Robotic Process Automation (RPA) solutions like UiPath have been market leaders for good reason. RPA has been an excellent tool for automating simple, repetitive tasks with logic-based scripting and screen-scraping technologies. Where it falls short, though, is in addressing complex use cases or when minor UI updates can disrupt an entire automation workflow. Further, the slightest variations in input data can break the process, leaving RPA developers scrambling to identify and fix bugs before mission critical processes halt.
After years of overlooking the flaws of RPA, enterprise technology leaders find themselves questioning whether their RPA investments are truly bringing value to the business or if the maintenance costs and headaches are just too high. Even the market leader in the RPA space, UiPath, continues to fall short of business and investor expectations. Fragile bots are constantly breaking, and the subsequent maintenance drives costs far higher than anticipated, creating an urgent need for a more resilient, intelligent, and cost-effective automation solution.
Kognitos has created a cost-efficient SaaS platform rooted in AI and natural language, marking a paradigm shift in enterprise process automation. RPA incumbents are no longer the best or only option available. This analysis highlights six key dimensions where the Kognitos platform outperforms UiPath: usability, implementation, efficiency, cognitive ability, cost structure, and scalability and governance.
Kognitos’ natural language processing fundamentally reimagines human-machine interaction by using plain English rather than a technical coding language to interpret and execute business processes. This allows both IT personnel and key business stakeholders to create complex automations from simple instructions. In contrast, UiPath’s visual workflow designer requires an elaborate understanding of programming logic and its deep nested menus. Kognitos is supported by a neurosymbolic AI architecture which combines generative AI with deterministic reasoning to support the full-scale needs and dynamic nature of enterprise processes.
UiPath’s “citizen developer” approach meant to reduce pressures on IT by allowing anyone to access automation. Instead, business users had to become pseudo-developers whose low-quality implementations further exacerbated the burden on already-constrained IT teams.
Instead of anything resembling “shadow IT” or even “shadow AI”, the innovative features of the Kognitos platform and its hyperautomation lifecycle (HAL) methodology create opportunities for IT to support a larger scope and quantity of business needs. In addition, business users and key stakeholders hold influence and direct visibility into relevant automations.
With Kognitos, there’s no need to learn coding concepts or fumble with drag-and-drop editors, team members simply document their processes in English. The platform understands written business documentation natively, such as the instructions contained in a standard operating procedure (SOP) document from finance or HR. When processes change, users simply update the documentation in Kognitos’ natural language interface or provide guidance through a chat interface. By reconsidering the way humans work with machines— AI interprets documentation rather than people learning programming—Kognitos enables businesses to unlock efficiencies through automation without the complexity that plagues UiPath’s technical environment.
Kognitos users can become proficient in as little as 8-10 hours, because they only need to learn the natural language constructs instead of abstract programming concepts. Compare this with the 80-120+ hours required for users to gain basic proficiency in UiPath Studio, and you’ll see that learning time is reduced by at least 90%. New Kognitos users can create automations in just two weeks, in contrast to three months or more with UiPath. Over time, users see a compounding effect to accessibility as Kognitos’ AI capabilities learn organizational terminology, understand context, and simplify communication.
Kognitos is set up on a serverless architecture that drastically reduces cost of ownership compared to UiPath’s licensing and infrastructure. UiPath’s pricing model burdens organizations with an abundance of required components that drive up annual expenses via direct costs:
Kognitos’ pricing is radically different from UiPath’s, offering a consumption-based model that reduces or completely eliminates recurring costs of specialized developer salaries, infrastructure, and licensing fees. Kognitos offers true enterprise scalability without infrastructure capacity constraints.
UiPath implementations rely on well-compensated RPA developers that earn upward of $120,000, in addition to infrastructure maintenance contracts that can exceed $40,000 a year. Kognitos eliminates these unnecessary expenses with a platform that allows business users to create automations in plain English without specialized technical expertise.
Case studies reveal that help desk tickets are 75% lower with Kognitos than with UiPath. As downtime and IT support needs diminish, indirect costs are further reduced. Kognitos platform is reliable and effective, reducing intervention needs, delivering faster ROI, and alleviating financial and operational challenges tied to RPA.
UiPath’s brittle automation scripts require constant upkeep. In fact, 30-40% of bot capacity is typically allocated to maintenance rather than new automation. Kognitos’ self-healing capabilities and patented conversational exception handling reduce maintenance costs by 90% or more through:
Post-implementation change requests that usually take 2-3 weeks to implement with UiPath can be completed in hours with Kognitos natural language instructions.
Kognitos embeds GPT-4o, Claude 3.5 Sonnet, Gemini 2, and custom models directly into workflow execution. This allows for contextual decision-making that remains impossible with UiPath’s rigid, rule-based framework.
This cognitive flexibility allows enterprises to automate processes with less than 70% structured data—a domain where UiPath would require an IDP point solution.
One of Kognitos’ differentiating capabilities is patented conversational exception handling. When the platform encounters an unexpected scenario, it asks a human for help in plain English. UiPath’s exception handling is limited to predefined error paths and would require manual intervention from developers when new issues arise. Kognitos can autonomously resolve 90% of exceptions on its own. Only especially complex cases are escalated to a business user, as the platform learns from every interaction.
Kognitos builds institutional knowledge through its Corporate Memory feature—a continuously updated repository of process decisions and resolutions. This enables:
UiPath lacks equivalent knowledge retention. In fact, with UiPath, the very first time an automated process is updated, it starts deviating from the documented process as described by the business users. There is no mechanism to learn from the past or provide anomaly detection capabilities based on the collected information of prior transactions.
Comparative analysis shows that Kognitos delivers 60-75% lower total cost of ownership (TCO) over three years versus UiPath.
| Cost Component | Kognitos | UiPath |
| Licensing Fees | $60k/year | $120k/year |
| Infrastructure | $0 (serverless) | $65k/year |
| Development | $50k/year | $180k/year |
| Maintenance/Support | $10k/year | $75k/year |
| Process Updates | $15k/year | $90k/year |
| 3-Year Total | $405k | $1.59M |
Kognitos demonstrates return on investment (ROI) in 3-5 months versus UiPath’s 12-18 month minimum due to:
UiPath’s opaque pricing model frequently leads to unexpected expenses from:
Kognitos’ all-inclusive pricing covers the complete automation lifecycle—infrastructure, AI skills, support, etc—without any hidden fees.
Kognitos excels at running high-volume, complex workflows and seasonal workload variation. The cloud-native architecture dynamically allocates resources to support practically unlimited concurrent automations. UiPath’s bot-based model has artificial scalability limits, and struggles to handle large scale deployments.
Stress tests show:
As a market leader in RPA, UiPath has an extensive list of technology partners. Kognitos has created an ecosystem of supported integrations to rival UiPath’s connectivity:
1. Universal Enterprise Connectivity
2. Intelligent Integration Capabilities
3. Enterprise-grade features
Kognitos integrations can be set up 75% faster than with UiPath, reduce 90% of integration maintenance, and achieve near-zero downtime because of the platform’s inherent AI monitoring and self-healing capabilities. API changes and updates are seamlessly managed throughout. The comprehensive integration framework allows rapid automation of complex workflows across any technology stack without sacrificing enterprise-grade security, reliability, or scalability.
No more managing or scheduling bots. Kognitos’ serverless architecture:
This serverless, elastic approach delivers perfect resource utilization compared to UiPath’s static bot allocation which underutilizes cloud resources. Kognitos delivers large reductions in cloud compute costs for bursty workloads when compared to UiPath.
Kognitos’ natural language processing (NLP) tools provide comprehensive audit capabilities, and the platform is capable of identifying regulatory risk factors in real-time. Each automation generates detailed records and process documentation in plain English, capturing:
This enables organizations to avoid black-box AI. They maintain complete visibility into the evolution history of each and every process and can use that data to:
In contrast, UiPath’s is significantly more cumbersome to review and audit. They follow a traditional approach that relies heavily on manual log analysis and demands extensive manual effort to piece together process histories.
With Kognitos, business users can input simple queries like “Show all PII handling steps in accounts payable automations” and the platform will generate comprehensive audit reports to ensure regulatory and industry-specific compliance including HIPAA, ISO 27001, SOC 2, PCI DSS, and more.
Kognitos documents all process changes, execution history, and AI learnings in plain English for unrivaled version control. Business users can easily review::
Because UiPath relies on technical expertise, version histories are inaccessible to 85% of business users. This inherently creates compliance and governance risk.
CIOs and other business leaders looking to invest in viable AI automation will find that self-improving agentic automation and the elimination of traditional coding implementations significantly reduces friction.
Kognitos delivers enterprise-grade automation in plain English, democratizing process automation for IT and business users. UiPath once changed the game for robotic process automation, but has critical limitations in cognitive flexibility, maintenance overhead, and total cost of ownership. When organizations can deploy automation faster at a lower cost, ROI follows in months, not years.
Kognitos is fundamentally reinventing how the world approaches automation. This isn’t simply incremental improvement over RPA technology, but a sweeping change for enterprises taking on digital transformation initiatives. The platform’s unique combination of natural language processing, self-maintaining AI, and serverless infrastructure position Kognitos as the successor to RPA tools like UiPath. If you’re currently comparing legacy RPA tools with more robust solutions like Kognitos, reach out to our team to discuss how we can help support your digital transformation and AI automation initiatives.
Disclaimer: All data was accurate at the time of collection on March 28, 2025. This competitor analysis article is intended for informational purposes only. While we have made every effort to ensure the accuracy and reliability of the information presented, market conditions and competitor strategies may change rapidly. Readers should conduct their own research and due diligence before making any business decisions based on this analysis. The authors and publishers of this article do not guarantee the continued accuracy of the information beyond the date of collection and are not responsible for any actions taken based on the content of this analysis.
Nine out of ten organizations are expected to suffer from IT skills shortages through the end of 2026. Talent shortages cause significant delays to innovation, beyond direct financial impact, which is estimated to be $5.5 trillion.
A lack of skilled talent threatens growth, scalability, and the ability to remain competitive. Talent shortages disrupt operational efficiency and stall digital transformation. As a result, CIOs are under constant pressure to address these issues and more—all while balancing cost efficiency with innovation.
Agentic Process Automation (APA) helps CIOs optimize their current workforce instead of seeking to hire talent that simply doesn’t exist. By automating routine tasks, technology leaders can free up their teams to focus on high-value work and develop new skills.
These are the talent and innovation problems highlighted by CIOs and how APA addresses them:
| Problem Area | Benefit of Agentic Process Automation |
| Talent shortages | Automate recruitment efforts, reallocate time from repetitive to strategic tasks, and avoid hiring specialized teams |
| Skill gaps | Upskill existing employees and preserve institutional knowledge |
| Inability to augment current talent | Enable teams to accomplish more with the same or fewer resources. Mitigate the impact of talent shortages and empower high-performing employees to innovate |
| Data silos leading to operational inefficiencies | Break down data silos for improved data connectivity and accessibility. Integrate legacy systems and unstructured data |
90% of tech leaders claimed recruiting and retaining talent as a moderate or major issue, compounded by the fact that technology skills are rapidly advancing. Furthermore, 93% of CIOs stated that AI would be essential to their success over the next five years. But the issue of hiring and retaining talent remains, complicating AI adoption efforts.
APA offers a solution for CIOs. These platforms can reduce the need for custom AI coding and implementation, address concerns about data security and compliance, and eliminate custom models creation in-house. Taken together, this significantly decreases the demand for dedicated AI talent and allows existing talent to assume the role without the need for a slew of specialized skills. Additionally, APA systems are low-maintenance, so organizations can reduce their reliance on software engineers, QA testers, and similar roles.
By implementing APA, organizations can more effectively allocate current team members to AI automation efforts and mitigate the effects of talent shortages. This approach allows companies to redirect their focus from hiring specialized AI professionals to leveraging existing talent more efficiently. APA automates routine tasks, freeing up employees to concentrate on more strategic, high-value work. As a result, organizations can maintain productivity and innovation without the constant pressure to hire and retain scarce talent.
Current teams may lack the skills required to handle new systems, creating a disconnect between workforce capabilities and technological advancements. A recent report by IDC suggests that skill shortages delay 67% of all digital transformation initiatives. Technology continues to outpace talent in the market, further exacerbating skills gaps. Those who do have in-demand skills are expensive, with 70% of them fielding multiple offers.
APA solutions employ technologies like natural language processing (NLP) and machine learning (ML) to create interactive learning experiences, flattening the learning curve and lowering barriers to entry for current employees. This allows a larger pool of people to become skilled, allowing them to easily upskill or cross-skill into more valuable roles at a fraction of the cost of new hires.
Furthermore, APA platforms should document and keep record of each process, preserving valuable institutional knowledge, even in the face of high turnover or retirements. As demand for tech talent increases, the ability to quickly get new team members up to speed and productive is imperative.
Every organization has standout team members who consistently deliver exceptional results. Wouldn’t it be incredible if their capabilities could be further enhanced? With the right tools, top performers can become even more impactful, inspiring greater efficiency and innovation across the organization.
APA augments the productivity of high-performing employees. By automating routine tasks like ticket management or campaign adjustments, APA frees up time for strategic, creative work. For example, engineers can focus on solving complex problems while AI agents handle administrative workflows.
Studies show that automation can boost productivity by up to 30%, amplifying the contributions of your best employees. By enhancing what top performers already do well, APA reduces pressure across teams and helps businesses achieve more without additional headcount.
Employees lose up to 12 hours a week searching for information trapped in silos. Data silos are isolated pockets of data that hinder cross-functional collaboration, innovation, and decision-making within the organization.
Agentic automation solutions act as a central hub that connects systems and disparate data sources in real-time. Having a centralized data repository makes it easier for departments to work together, avoid mistakes, and make smarter decisions. The result? Projects get done faster. Operations run more smoothly. Costs go down.
Let’s demonstrate the value of APA in this context with an example: Imagine a bank with multiple divisions like retail banking, wealth management, and commercial lending. As teams collect valuable customer data, it remains trapped within business line silos. The bank lacks a holistic view of customer behavior and preferences, lowering customer lifetime value and increasing the likelihood of churn. APA breaks down business line silos to share relevant data that can grow into a complex network of automation. Ultimately, this means the bank can provide a more personalized experience for its customers.
Agentic Process Automation empowers CIOs to resolve talent shortages and skill gaps, accelerating innovation and reducing operational inefficiency.
This technology enables CIOs to make the most of their existing workforce without adding headcount. Automation frees up valuable time and resources so teams can focus on strategic initiatives and creative problem-solving without the burden of work they don’t want to do. As CIOs navigate the challenges of digital transformation, APA stands out as a key enabler in balancing operational efficiency with the pursuit of innovation.
If you are a forward-looking CIO looking to drive innovation, Kognitos can help. Reach out to a member of our team, and we can work together to position you and your organization for future growth and success.
Agility and the ability to scale operations quickly are critical priorities for any large organization. As the market rapidly evolves and grows more competitive, scalability and agility enable organizations to pivot swiftly in response to changes in the economy, customer demands, and available resources. CIOs must support not just the IT department, but the entire organization by building highly scalable systems that support business expansion while maintaining performance and efficiency.
According to a Gartner report, 74% of CEOs believe AI is the technology that will have the most impact and influence on their industries. As a result, CIOs are under constant pressure to demonstrate value and tangible business impact from their AI investments. As CIOs look to meet lofty expectations, agentic process automation (APA) is poised to finally deliver on the elusive promise of agile and scalable enterprise automation.
| Problem Area | Benefit of Agentic Process Automation |
| Limited Scalability of Legacy Automation Solutions | APA uses serverless infrastructure and AI agents to scale dynamically without additional infrastructure or talent investments |
| Too Many Point Solutions | APA integrates with existing tools, reducing the need for multiple point solutions by leveraging built-in AI skills |
| High Costs of Scaling Legacy Systems | Agentic automation bridges legacy systems with AI, offering a cost-effective pathway to phase out outdated infrastructure and scale without increased operational costs |
| The Talent and Skills Gap | APA has a lower barrier to entry, lowering skills requirements and making it easier to upskill or cross-skill team members |
Automation has been on the radar of enterprise organizations since the early 2000s in an attempt to streamline workflows and improve operational efficiency. As process automation evolved, Robotic Process Automation (RPA) solutions emerged. While RPA offered some benefits as compared to previous Business Process Management (BPM) solutions, it faced challenges in scalability and agility due to its limitations in handling complex processes, frequent breakdowns leading to high maintenance costs, and ever-increasing direct costs.
APA solutions employ a serverless infrastructure, capable of scaling to the organization’s needs without the same infrastructure and skilled talent investments that make RPA untenable at scale.
AI agents make intelligent decisions based on your organization’s standard operating procedures, allowing for more agile and responsive operations (e.g., 24/7 support). Unlike RPA, APA can adapt to changing conditions without the classic software development lifecycle headaches, ensuring that business processes remain optimized even as variables fluctuate.
APA solutions are also capable of executing multiple tasks simultaneously instead of one after the other (serial), which accelerates process execution times and significantly improves productivity.
One of the biggest challenges organizations face in scaling operations is the fact that they currently employ too many point solutions—specialized software tools designed to address a specific problem. Large enterprises used an average of 112 SaaS applications in 2023 and new data suggests that this number is only continuing to increase. Point solutions undermine organizational agility. They are difficult to integrate and are a leading contributor to technical debt—a challenge cited by 91% of CTOs.
Agentic process automation can integrate seamlessly with various existing tools and platforms, learning from enterprise data to provide highly contextualized, end-to-end process automation. Furthermore, since APA is AI-native, it comes with a plethora of built-in skills that eliminate the need for many point solutions entirely. This is why many leading technologists, including Microsoft’s Satya Nadella, say that the end of SaaS may have already begun.
APA solutions come with minimal friction in terms of adoption, applicability, and infrastructure, empowering CIOs to replace point solutions and drive scalability.
Legacy systems, particularly on-premise installations, continue to constrain organizational scalability and agility in the modern era. While RPA and similar technologies have provided temporary relief by integrating with modern, cloud-based tools, they do not address the core limitations of legacy systems, which often tether organizations to outdated infrastructure.
APA offers a comprehensive solution that bridges legacy systems with cutting-edge AI technology. This not only facilitates smoother integration, but also provides CIOs with a practical pathway to phase out legacy systems in favor of serverless, cloud-native solutions.
Unlike legacy systems that require significant maintenance and hardware investments, APA solutions are inherently scalable. They can dynamically handle increases in workload without corresponding increases in operational costs, making them ideal for organizations seeking scalability and cost-efficiency.
59% CIOs admitted that staffing and skills shortages detract from time spent on strategic initiatives. This struggle has become a major hindrance for organizations, as existing talent lacks the skills to automate with incumbent solutions and requires support from larger maintenance teams to automate additional processes.
Agentic solutions bridge skills gaps by augmenting human capabilities instead of replacing headcount. Automating routine, non-strategic tasks frees employees’ bandwidth to focus on work requiring critical thinking and decision-making. AI agents deployed by APA solutions are capable of providing users with contextual information, simplifying process automation. This helps organizations avoid investing heavily in specialized human resources.
Agentic process automation is a powerful tool helping CIOs overcome scalability and agility challenges. It provides infinite scalability, process optimization, end-to-end workflow automation, run parallelization, and autonomous decision making. CIOs leveraging AI automation can enhance operational efficiency and drive strategic growth, moving from a cost center to a revenue generator in their organizations.
If you are considering how agentic process automation can help your organization scale, please reach out to our team for a personalized demo of how Kognitos can support your specific use cases.
Kognitos’ innovative hyperautomation lifecycle (HAL) platform offers an end-to-end solution that automates the entire lifecycle of automation and sets Kognitos apart as the leader in agentic process automation (APA). Built on a serverless infrastructure, HAL combines generative AI with deterministic logic to deliver reliable, repeatable, and hallucination-free AI agents.
The hyperautomation lifecycle begins by auto-writing a workflow based on an SOP, simple instructions, or a predefined prompt. Your process becomes a powerful AI agent, completely managed within the HAL platform. Processes are then auto-deployed with the click of a button, instead of months of setup and testing as with traditional RPA deployment. Any updates to your AI agents are auto-tested to validate that they will function reliably under any conditions, including edge cases.
Then what? Let’s explore the next stage of the hyperautomation lifecycle: auto-monitor.
As soon as an automation is deployed, HAL’s auto-monitor stage continuously observes and assesses performance, health, and security of every active automation within the platform.
The auto-monitor stage of HAL creates an accessible system of record in plain English. Business users can easily understand the status of their automations—no technical expertise or coding knowledge required. This reduces IT bottlenecks and simultaneously democratizes access for key stakeholders within the organization.
HAL’s proactive approach to exception handling identifies potential issues without breaking the automation. The system notes exceptions, pauses, and asks for human guidance if needed. The review process is quick and easy, so AI agents can deliver consistent results at peak efficiency.
Auto-monitor’s impacts extend beyond simply observing and flagging active automations. The hyperautomation lifecycle is a self-maintaining ecosystem where each stage can actively communicate with the others. For example, auto-monitor notes issues and gets a human involved when it needs help. Over time, the need for human intervention reduces. The Kognitos brain learns how to auto-debug similar exceptions, auto-write new automations to address issues, and auto-test edge cases after adjustments are made.
This creates truly autonomous AI agents capable of improving performance over time without the need for manual intervention.
With HAL, organizations can:
Transform the way your organization approaches automation by ditching fragile RPA workflows and exploring HAL. Kognitos stands apart as an end-to-end APA solution that automates tasks, but also manages the entire lifecycle of AI agents.
If you’re a CIO or technology leader looking to adopt AI that can provide massive ROI in months, not years, reach out to our team to book a custom demo of Kognitos’ HAL.
CIOs are under tremendous pressure to reduce costs, both within their own IT departments and by directly supporting other business lines. Capgemini Research reports that 56% of business leaders expect to prioritize cost reduction over revenue growth for this fiscal year.
Even though CIOs are feeling pressured to cut costs, 50% of organizations report that they will continue to increase strategic investments. Agentic process automation (APA) is one powerful investment that can achieve multiple goals for CIOs by driving massive ROI, cutting costs, improving operational efficiency, and increasing productivity. In fact, intelligent automation technologies—which APA falls under—are expected to reduce costs by 22%, while also increasing revenue by 11% in the three years after implementation.
While legacy automation solutions including business process management (BPM) and robotic process automation (RPA) delivered some tangible benefits to CIOs, their untenable maintenance costs and low agility in support of enterprise scale ultimately limited both adoption and impact. In opposition, APA can quickly unlock benefits for CIOs through a combination of natural language processing, generative AI, and built-in skills.
| Problem Area | Benefit of Agentic Process Automation |
| Mounting Manual Labor Costs | Directly reduces labor costs by automating routine manual tasks of varying complexity |
| Operational Inefficiencies | Improves efficiency, resulting in reduced work hours and lower labor costs |
| Increasing Cybersecurity Costs | Bridge talent and skills gaps and drive down cyber risk with AI automation |
| Mounting Technical Debt | Consolidate point solutions and drastically reduce maintenance costs of legacy systems |
APA significantly reduces costs associated with manual labor. Examples include data entry, customer service, invoice processing, inventory management, and other repetitive tasks. Take financial services, for example: loan application processing tasks such as document verification and credit score assessment can be quickly automated, so loan officers can focus their efforts on more complex cases and building stronger customer relationships. McKinsey estimates that tasks comprising up to 30% of working hours could be completely automated, translating to trillions of dollars in savings.
APA is far more adaptable and intelligent than previous technologies like Robotic Process Automation (RPA), which operate within rigid frameworks and require significant development work when processes change. Contrarily, APA is capable of learning and adjusting automations in real-time with minimal human intervention. This adaptability enables complex workflows at enterprise scale, without sacrificing performance or efficiency, making it an ideal solution for businesses looking to scale their operations without proportionally increasing their workforce.
Bain’s Automation Scorecard 2024 Report reports that the top quartile of organizations prioritizing automation investments were able to cut costs by an average of 37%. On the other hand, organizations investing 5% or less of their IT budgets in automation could only manage to cut costs by 8%.
APA has the potential to be even more impactful than legacy automation solutions like RPA that require substantial upfront investment, specialized developers, and significant maintenance. Kognitos uses pre-trained models that operate in plain English, enabling multiple business users to automate processes and reducing IT bottlenecks while preserving oversight.
Not only are tasks being automated, but implementation and maintenance headaches are significantly reduced, empowering employees to work as efficiently as possible and pushing agility in the organization.
Cybersecurity is a significant cost center for CIOs, and is expected to remain so in the face of increasing cyber threats and more sophisticated data breaches. In 2024, the average cost of a data breach climbed by 10% to $4.88M.
In addition to infrastructure, pervasive cyber skills gaps and talent shortages further drive up the costs associated with cybersecurity. Attracting and retaining cyber talent is expensive, and demand far outweighs supply, making cybersecurity a top cost center for CIOs.
APA solutions help bridge skills gaps by making more efficient use of cybersecurity personnel. Rather than spending time continuously monitoring networks for potential breaches or isolating malicious traffic, team members can deploy AI agents capable of autonomously addressing issues that arise. Organizations can cut costs and improve cybersecurity without adding headcount.
79% of tech leaders cite technical debt as a significant hurdle in achieving their business objectives. So much so that they dispatch anywhere from 25%-40% of their developers’ time to addressing tech debt.
CIOs have struggled to replace point solutions and retire legacy systems without business disruption. The emergence of APA provides an opportunity to consolidate point solutions and cut costs for both the system itself, as well as its maintenance costs.
APA has the potential to be even more impactful than legacy automation solutions like RPA that require significant upfront investment, specialized developers, and substantial maintenance. Agentic platforms can streamline workflows of similar or greater complexity, incorporating previous point solutions into a single end-to-end platform and further accelerating cost savings.
Agentic automation solutions provide CIOs with the opportunity to do what previously seemed impossible—reducing costs while optimizing resources to drive AI innovation in the organization. As leaders and business executives, CIOs must drive strategic change across key focus areas to deliver substantial cost savings.
AI automation will be crucial for CIOs to grow their strategic influence and drive their organizations forward. If you are a forward-leaning leader looking to prioritize strategic automation investments at your organization, reach out to the Kognitos team to see how we can help position you for greater success.
If your organization relies on traditional robotic process automation (RPA) tools like UiPath, you might be grappling with hidden costs, fragile workflows, and developer bottlenecks. It’s time to ask: is there a smarter way to automate?
At Kognitos, we’re redefining automation with our AI-native HAL (hyperautomation lifecycle) platform that turns simple instructions into self-maintaining AI agents. We’re automating the most complex processes in natural language with enterprise scalability. Forward-thinking CIOs are making the switch. Here’s why you should consider it, too.
There’s no doubt that UiPath revolutionized RPA, but its limitations have become impossible to ignore:
Sound familiar? You’re not alone.
Kognitos isn’t just another RPA tool—it’s a paradigm shift toward agentic process automation that’s actually in production. Here’s how we outpace UiPath:
Kognito’s HAL platform doesn’t require specialized developers to create a workflow. Business users input simple instructions using natural language and HAL auto-writes the automation. For example, writing an automation might be as simple as typing “Process invoices from Outlook, validate amounts, and update SAP.”
There’s no learning curve with HAL’s intuitive interface. CIOs and technology leaders can choose to empower HR, Finance, and Operations departments to build automations themselves.
Our AI agents are adaptive, automatically adjusting and addressing any UI changes, differing data formats, or updates to processes—without manual intervention. Automations can become fully autonomous while also maintaining a trusted system of record.
HAL’s auto-debug and auto-test features fix errors in real-time, reducing maintenance costs by up to 80%.
Kognitos can integrate directly via API with your systems, like SAP, Salesforce, and more, for faster and more reliable workflows.
Our serverless infrastructure provides scalability to your organization, while also maintaining security with staging environments, role-based access, and audit trails to ensure compliance.
Deploy automations in days, not the months you can expect with UiPath. One Kognitos Fortune 500 client automated their invoice processing workflows in three days, versus six weeks on UiPath.
Provide a faster path to ROI with 50% lower total cost of ownership (TCO) as compared to incumbent RPA solutions like UiPath. Overnight, Kognitos can help slash licensing, developer, and maintenance.
Legacy RPA tools like UiPath aren’t AI-native, and are trying to adapt to the AI era. As competitors adopt agentic AI and hyperautomation, clinging to outdated platforms risks loss of efficiency, missed opportunities, and stagnation of innovation.
Let’s play out a scenario. You’re a CIO tied to UiPath. Manual bot upkeep drains IT and developer resources. Not only do they lose efficiency on maintaining brittle RPA workflows, they become a bottleneck for the organization. You miss opportunities at every turn to automate complex, dynamic processes, because you don’t want to overwhelm already strained developers. IT teams are stuck fixing bots, not driving strategy. IT is seen as simply a cost center, instead of a team bringing innovation to the organization.
Worried about disruption? Don’t be.
Kognitos offers a free pilot program, so CIOs can test-drive the platform with their most painful UiPath workflow. As your company migrates from UiPath, our team supports in converting existing automations to achieve zero downtime. Lastly, our dedicated onboarding team will provide you with enterprise training and on-demand resources to set your team up for success.
The future of automation isn’t about more code—it’s about more clarity.
Kognitos turns business users into automation heroes, slashes costs, and keeps workflows agile in the face of change. Are you ready to leave UiPath’s limitations behind? Request a 15-minute demo or sign up for free community trial access to HAL to see how Kognitos can transform your automation strategy in weeks, not months.
Automate smarter. Automate simpler. Automate with Kognitos.
Agentic process automation is quickly becoming reality, and businesses are actively pursuing applications in high value use cases in order to stay competitive. Testing workflows for reliability across multiple scenarios—not to mention accounting for edge cases—can be time-consuming and expensive.
Kognitos’ auto-test feature is a game-changer for automation as we know it. It is designed to automatically simulate various scenarios and edge cases to ensure the automation will perform as expected, simplifying and accelerating the process of creating autonomous automation workflows.
Kognitos is an end-to-end neurosymbolic AI platform that automates every stage of the automation lifecycle into one seamless system, eliminating the need for prolonged implementations and taxing upkeep. It combines cutting-edge generative AI with deterministic logic to create AI agents capable of automating even the most complex processes.
Business users are empowered to automate any process without bots, specialists, coding expertise, or extensive infrastructure. This blog dives deeper into the auto-test feature.
As automations progress through Kognitos’ patented process refinement, AI agents continuously optimize workflows as needed. Auto-test is akin to regression testing in the traditional software development lifecycle. As changes are automatically applied to an automation, auto-test validates that workflows will continue to function reliably under any conditions, particularly after significant updates to an automation already in production. Here’s how it works:
After code changes or updates during the auto-write or auto-debug stages, auto-test will generate and run simulations for a multitude of scenarios, including edge cases. This ensures that automations can grow to be fully autonomous where desired, while continuing to perform as expected under different conditions without manual intervention.
Let’s explore an example. A user might automate 1,000 runs a day processing insurance claims. When Kognitos meets an exception, a business user reviews and applies a learning to that specific run using the auto-debug and auto-write features. Because the automation has now changed substantially, the AI automatically reviews similar runs before applying that learning to all future runs. Let’s imagine that Kognitos chooses, say, 200 previous cases to auto-test. The results validate that the expected outputs are produced with the updated automation in place, and that it can be applied to all future runs.
Any business user can initiate and review tests. The interface displays test results in plain English, so automations are accurate and reliable without the need for technical coding expertise. Within the test suite, Kognitos shows an easy visual comparison for automation outputs following a change. When outputs are validated against expected results, the run is color-coded green to make it easy to read at a glance.
In contrast to the hours or days spent regression testing legacy robotic process automation (RPA), Kognitos can auto-test workflows in minutes. As AI agents auto-write and auto-debug automations, auto-test serves as a litmus test before applying similar changes to all future runs. It finds use cases for previous runs and tests them, for example, 200 times to validate the updated automation. If there are unexpected outputs, a business user can quickly validate and make adjustments based on the test results, then instantly run the simulations again.
Manual testing is labor-intensive and prone to human error. But beyond that, AI systems have been known to hallucinate from time to time. Auto-test addresses each of these concerns in turn. Not only has your business saved significant time and resources, but this process also verifies the integrity of the results. Kognitos is revolutionizing how businesses approach automation by making it faster, simpler, and more reliable.
If you’d like to learn more about Kognitos, reach out to a member of our team or sign up for free community trial access today.
Kognitos’ HAL (hyperautomation lifecycle) platform is a game-changer for organizations looking to implement agentic AI automation, save time, deliver value, and reduce technical debt. As point solutions for automation and AI agents emerge, Kognitos stands apart as a platform that meets complexity head-on, while remaining user friendly.
HAL is automating the entire lifecycle of automation, beginning with its innovative auto-write feature.
At its core, hyperautomation enables organizations to automate processes at scale. The demand for automation has always been high, but the resources required to support traditional automation kept large-scale adoption out of reach. HAL is designed to bring together each stage of the hyperautomation lifecycle, providing a single, integrated solution that not only automates tasks, but also manages and optimizes them.
The platform is built upon a cutting-edge, neurosymbolic hybrid AI that combines the creativity of generative AI with deterministic logic to deliver accurate, repeatable, and hallucination-free AI agents. In short, HAL is an end-to-end automation solution. The five steps of the hyperautomation lifecycle are:
Let’s dive deeper into HAL’s auto-write functionality.
Each new automation created in HAL begins with the auto-write feature. Users can create sophisticated workflows from simple instructions, eliminating the need for complex coding or technical expertise.
Where in the past a new process automation may have required months of planning and design, with HAL you can have an automation with as little as a prompt or SOP (standard operating procedure) document. Here’s how it works:
Users input their SOPs or simple instructions into the platform in plain English. HAL can even prompt users to auto-generate instructions for common use cases like generating reports in Excel, processing invoices, data reconciliation, and more.
HAL reviews the prompt or the instructions you provide, then generates a detailed plan in deterministic English, so both the machine and the human can understand. This crucial, intermediate step is what makes AI trusted, auditable, and safe for use in mission critical business processes.
After outlining the steps above, HAL auto-writes the automation. You review the automation, and simply click “Apply” if everything looks correct.
To run your automation through the rest of the stages of HAL, click “Accept all” and then run the process. It’s that simple. Start to finish, you can create your agent in minutes.
Auto-write makes creating powerful enterprise automations simpler than ever before. It can streamline a variety of use cases. Our customers have found particular success with intelligent document processing (IDP) and Excel-based tasks, such as invoice processing and data consolidation.
Instead of investing time and resources on programming bots, HAL can create self-sustaining AI agents capable of automating complex business processes. If you have an SOP, you now have an AI agent.
HAL and its auto-write feature are revolutionizing the way the industry does automation. If you’re ready to experience the power of auto-write and the full capabilities of HAL, sign up for free community trial access to HAL, and create your first AI agent today.
Hyperautomation and agentic AI will allow organizations to streamline processes, boost efficiency, and stay competitive in ways that haven’t been seen before. Enterprise technology leaders have a clear opportunity to harness these recent technological developments to drive organizational success by combining the power of hyperautomation with the execution of AI agents.
Originally coined by Gartner, hyperautomation is more than just another buzzword in the automation landscape (see: agentic AI)—it’s an enterprise-level strategy that enables automation at scale. Whatever can be automated, must be automated.
Hyperautomation was originally conceived of as a network of tools to automate virtually every process within an organization. In the years since Gartner first introduced the concept, the definition has shifted slightly. Rather than relying on a complex tech stack to automate workflows within an organization, many leaders are looking to consolidate incumbent platforms while still achieving the same level of automation.
Incumbent automation providers have met challenges every step of the way with slow progress, high costs, limited scale, and fragility. Hyperautomation has the potential to overcome these challenges.
While many solutions offer automation components that work in tandem with additional platforms to hyperautomate processes, Kognitos’ HAL platform provides an integrated solution that encapsulates every stage of the hyperautomation lifecycle. HAL is designed not just to automate tasks, but also to manage and optimize them.
The concept of hyperautomation looks beyond what automation can achieve today to emphasize a continuous lifecycle of improvement. The hyperautomation lifecycle provides a systematic approach over these key stages:
HAL has created a unified automation ecosystem, as opposed to the disparate systems and platforms in legacy hyperautomation efforts. The cloud-based, scalable platform seamlessly integrates with existing technologies, allowing CIOs to execute upon hyperautomation strategies without overhauling their current tech stack.
Minimize exposure to external threats with HAL’s scalable infrastructure. Most endpoints, except for user interfaces (UI) and management APIs, are inaccessible through the public internet. The UI endpoints are safeguarded through API gateways, ensuring an added layer of protection. All this is made possible by the fact that our platform is underpinned by a serverless technology, allowing you to avoid maintaining underlying infrastructure, reducing costs and driving down total cost of ownership.
We combined intuitive generative AI with deterministic programming to create HAL—the trusted platform that combines accuracy with flexibility. Throughout the lifecycle, HAL can make autonomous decisions, but recognizes when it needs human input, and trusts the expertise of the team.
When HAL meets an exception, it asks for human input in natural language. Our patented conversational exception handling allows anyone who knows the process to provide the platform with feedback, so it can quickly adapt to drive perpetual refinement
For technology leaders eager to leverage cutting-edge technologies, the potential rewards of hyperautomation are immense: greater efficiency, enhanced operational agility, and the capacity to foster a culture of constant learning and adaptation.
As the landscape of business continues to change, hyperautomation is not just an opportunity—it’s a mandate. With Kognitos’ Hyperautomation Lifecycle platform, organizations have the means to not only catch up with the future but to lead it. Embrace hyperautomation with HAL and craft the dynamic, intelligent enterprise of tomorrow.
Bank Risk Management stands as an absolute imperative in the highly regulated and interconnected world of finance. It’s the structured process by which financial institutions identify, assess, monitor, and mitigate various risks that could jeopardize their capital, earnings, or reputation. This comprehensive approach is not just about avoiding losses; it’s about ensuring stability, fostering growth, and maintaining public trust.
Effective Bank Risk Management empowers financial leaders, CIOs, and technology heads to navigate a landscape filled with unpredictable challenges. It transforms potential threats into manageable scenarios, allowing banks to operate securely and efficiently. Understanding this crucial discipline is foundational for anyone involved in the strategic direction and operational integrity of a banking institution.
The financial sector operates under constant scrutiny and faces dynamic global economic conditions. This makes the importance of risk management in the banking sector paramount. Banks handle vast sums of money, facilitate complex transactions, and are entrusted with the financial well-being of individuals and businesses. Without robust risk frameworks, instability can quickly cascade, leading to severe economic repercussions.
A well-defined risk management strategy safeguards against financial shocks, supports regulatory compliance, and protects stakeholder confidence. It’s the backbone of resilience, enabling banks to absorb unexpected losses, adapt to market shifts, and continue serving their clients effectively. Proactive Bank Risk Management builds a foundation of trust, essential for any institution seeking sustained success.
Banks contend with a multitude of potential threats that can impact their operations and profitability. A clear understanding of the various types of risks in banking sector is the first step towards effective mitigation. These risks are interconnected and require a holistic risk management strategy to address.
Primary categories include:
Each of these types of risks in banking sector demands specialized attention and integrated risk management solutions.
Effective Bank Risk Management isn’t a one-time task; it’s a continuous, cyclical process involving several critical stages. This structured approach ensures that risks are systematically identified, assessed, and managed. Understanding How Does the Risk Management in the Banking Process Work involves recognizing these interconnected steps.
The five key stages are:
This cyclical process ensures that a bank’s risk management strategy remains agile and responsive to evolving threats and opportunities.
The complexity of modern Bank Risk Management demands more than traditional methods. The integration of Artificial Intelligence (AI) and automation has emerged as a game-changer, offering powerful risk management solutions that enhance efficiency, accuracy, and real-time responsiveness. These technologies are crucial for strengthening a bank’s overall risk management strategy.
AI-driven analytics can process vast datasets quickly, identifying subtle patterns and predicting potential risks with far greater precision than manual methods. For instance, AI can significantly enhance cybersecurity defenses by detecting anomalous network activity in real time. Automation, conversely, streamlines repetitive compliance tasks, reduces human error in data processing, and accelerates various risk assessment and reporting workflows. This synergy empowers banks to shift from reactive measures to a proactive, predictive approach in managing complex risks, improving credit assessment, and enabling continuous monitoring.
Many financial institutions seek advanced risk management solutions but find traditional tools fall short. Kognitos offers a fundamentally different approach to Bank Risk Management, by transforming automation with natural language and AI reasoning, making enterprise-grade AI accessible to business users.
Kognitos empowers business teams to automate processes crucial for risk management using plain English. This bridges the gap between IT and risk/compliance operations, allowing for greater agility and control. Our platform leverages a neurosymbolic AI architecture that ensures precision and eliminates AI hallucinations, providing robust AI governance and control essential for mitigating operational and compliance risks. This positions Kognitos as a key tool that helps banks in addressing various risks effectively.
Kognitos innovations, like hundreds of pre-built workflows for finance and legal and built-in document and Excel processing, mean that common risk-prone processes, such as contract review or regulatory reporting, can be automated with inherent accuracy and traceability. Automatic agent regression testing ensures that as regulatory environments change, automations can adapt confidently, supporting a robust and evolving risk management strategy.
The application of advanced automation and AI through platforms like Kognitos provides tangible benefits for Bank Risk Management. These practical scenarios demonstrate how financial institutions can deploy innovative risk management solutions.
Consider these real-world examples:
These applications underscore how a sophisticated risk management strategy powered by AI and automation transforms the banking sector’s ability to identify, mitigate, and monitor risks effectively.
To develop a truly robust risk management strategy, banks must embrace continuous innovation and a holistic view of their operational landscape. The dynamic nature of the financial industry necessitates ongoing adaptation and technological adoption.
Key ways to strengthen your Bank Risk Management framework include:
By focusing on these areas, banks can build a resilient and forward-looking Bank Risk Management posture.
The future of Bank Risk Management is inextricably linked to advanced technological adoption. As regulatory environments become more complex and cyber threats more sophisticated, banks must move beyond traditional compliance checkboxes to truly intelligent, adaptive risk frameworks. The importance of risk management in the banking sector will only amplify.
Kognitos is uniquely positioned to drive this transformation. By empowering institutions with natural language AI for automation, we provide truly innovative risk management solutions that enhance visibility, streamline compliance, and build inherent resilience. For financial leaders, understanding Bank Risk Management is no longer just about compliance; it’s about leveraging AI and automation to secure a competitive edge and build enduring trust in an unpredictable world.
