Product & Innovation

Auto-Test AI Agents with Kognitos

Kognitos

Key Takeaways

Kognitos’ auto-test feature automatically validates agentic process automation workflows so they keep performing reliably as they change. The post explains that auto-test works like regression testing in traditional software: when a business user resolves an exception through auto-debug and auto-write, the AI automatically simulates many past runs and edge cases, for example, replaying 200 prior insurance-claim cases, before applying that learning to all future runs. Results appear in plain English with color-coded pass/fail comparisons, so no coding expertise is required. Built on a neurosymbolic AI platform that pairs generative AI with deterministic logic, auto-test cuts the hours or days of manual RPA regression testing down to minutes while guarding against hallucinations. The takeaway: auto-test lets teams grow toward fully autonomous automation with confidence, speed, and verifiable integrity.

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.

What is Kognitos’ Neurosymbolic AI Platform?

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.

How Does Auto-Test Work?

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:

Automatically Simulate Various Scenarios

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.

Test Without Coding

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.

Auto-Test AI Agents with Kognitos’ HAL Platform — Auto-Test AI Agents with Kognitos

Save Time with Kognitos

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.

Frequently Asked Questions

The Kognitos auto-test feature is an automated testing capability within the Kognitos neurosymbolic AI platform that simulates various scenarios and edge cases to ensure automation workflows perform as expected. It functions similarly to regression testing in traditional software development, validating that automations continue to work reliably after significant updates or code changes. Auto-test runs automatically as part of the platform's continuous optimization cycle, removing the need for manual test setup or intervention. It is designed to give businesses confidence that their AI agents will behave correctly across all conditions before changes are applied to future runs.

After code changes are applied during the auto-write or auto-debug stages, auto-test generates and runs simulations across a broad range of scenarios, including edge cases. The platform selects a representative sample of previous runs, for example 200 historical cases, and reruns them against the updated automation to validate that expected outputs are still produced. Results are displayed visually in plain English, with color-coded indicators so business users can quickly identify passing and failing scenarios. If unexpected outputs appear, a business user can review the results, make adjustments, and immediately rerun the simulations without any coding.

The primary benefit of Kognitos auto-test is the dramatic reduction in time spent validating automations, completing in minutes what would traditionally take hours or days with legacy RPA tools. It also reduces the risk of human error that comes with manual testing and guards against AI hallucinations by verifying that updated automations produce consistent, accurate outputs. Business users without technical backgrounds can initiate and review tests independently, lowering dependence on developers or automation specialists. The result is a faster, more reliable automation lifecycle that allows organizations to scale their AI agent deployments with greater confidence.

Legacy RPA regression testing is a labor-intensive process that typically requires technical specialists and can take hours or days to complete after any code change. Kognitos auto-test compresses this process to minutes by automatically selecting test cases, running simulations, and surfacing results in plain English without requiring any coding. Traditional RPA testing is also prone to human error and incomplete coverage, while Kognitos automatically identifies and tests a representative cross-section of scenarios including edge cases. This means AI agents on the Kognitos platform can be updated and validated far more quickly than bots on conventional automation platforms.

A practical example is an insurance company running 1,000 automated claims-processing runs per day on Kognitos. When an exception occurs, a business user reviews it and applies a learning through the auto-debug and auto-write features, which changes the automation. Before that change is applied to all future runs, auto-test automatically selects around 200 previous claims cases and reruns them against the updated workflow. The results confirm whether the updated automation produces the correct outputs across all those historical scenarios, and only then is the change rolled out broadly. This protects the organization from inadvertently introducing errors into a high-volume production workflow.

No, Kognitos auto-test is designed so that any business user can initiate and review tests without coding expertise. The test suite displays results in plain English with color-coded visual comparisons, making it easy to understand which outputs matched expectations and which did not. When discrepancies appear, users can review them, apply corrections, and immediately rerun tests from the same interface. This accessibility means that operations teams, finance departments, and other non-technical staff can confidently manage the testing and validation of their AI automation workflows on their own.