Webinar: hallucination-free ROI beyond bots and prompts

RPA programme owners and centres of excellence ready to move beyond rules and bots, CIOs and CFOs scoping their next automation wave, BPO and shared-services leaders looking for differentiated outcomes, and any organisation that has already invested in UiPath, Automation Anywhere or Power Automate and wants to know where agentic AI complements those investments.

Binny frames it bluntly: about 80% of business-critical information still lives in unstructured form (emails, contracts, documents), and a 98%-per-step process loses accuracy fast across 50 steps. RPA bots cannot read the unstructured part reliably, and copilots help an individual but do not own multi-step processes end-to-end. Agentic, hallucination-free AI on a deterministic runtime is what fills the gap.

Hallucination-free means the LLM is only allowed to interpret language; every decision is executed against your written policy by a deterministic runtime. When the model is unsure it raises a plain-English exception instead of guessing. There is no scenario where a customer-facing decision is taken on the strength of an LLM's confidence score alone, which is what makes the platform safe for finance, insurance and healthcare workloads.

qBotica brings deep automation services, customer ownership and existing RPA estates; Kognitos brings the platform and the symbolic layer. Together they have shown working solutions to brand-new customer problems in 24-48 hours of receiving sample data, where a traditional model-training approach would have taken 2-3 months. The session walks through how the partnership scopes, builds and operationalises joint deployments.

No. The recommendation from both CEOs is the opposite: keep what already works, and layer Kognitos on the parts of the process that RPA cannot reliably handle (unstructured documents, exceptions, judgement decisions). Kognitos can orchestrate UiPath, Automation Anywhere and Power Automate bots as steps in a larger agentic workflow and progressively absorb the highest-cost manual touches around them.

Joint examples include quote and contract intake (an example where Kognitos returned a working solution within 48 hours of receiving sample quotes), document-heavy AP and customer onboarding workflows, exception-handling backlogs that have grown around legacy RPA, and high-volume back-office processes where a 90%+ straight-through rate has a step-change effect on cost-to-serve.

Mahesh's analogy: where 5 years ago you had to spend 2-3 months training a special-purpose model, today you can describe the policy in English and have a Kognitos agent producing useful outputs within 24 hours. The cost and timeline of an enterprise AI build now look more like a software-engineering sprint than a data-science project, and that compresses payback timelines dramatically.

Look for processes that combine three traits: meaningful volume, unstructured inputs (email, PDF, image, free-text), and policy that today is enforced by humans. If a process has all three, it is a strong candidate. Bring 20-50 representative samples to a Kognitos and qBotica scoping call and you'll have a quantified ROI estimate within days.

Binny Gill is reachable at binny@kognitos.com and on LinkedIn. Mahesh Fanagum is active on LinkedIn and reachable at mahesh@qbotica.com. For a scoped pilot, request a personalised demo through the Kognitos or qBotica websites; both organisations will jointly evaluate whether your use case is the right fit for agentic, hallucination-free automation.