Home/Videos/Beyond Bots & Prompts: High ROI Use Cases for Hallucination-Free AI Automation with Kognitos and qBotica
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Video: high-ROI automation without brittle prompt loops
Binny Gill (Kognitos) and Mahesh Anantapanagamanam (QBotica) on hallucination-free AI automation — and an outcomes-based delivery model that replaces TNM hours and license bulk-buys.
About this webinar
A joint Kognitos and QBotica webinar focused on the high-ROI use cases that finally become viable when AI automation is genuinely hallucination-free — and the delivery model that pays for outcomes, not for PowerPoints.
Speakers
- Binny Gill — founder and CEO of Kognitos. 30 years writing code; started Kognitos with the conviction that English-as-code (not yet another programming language) is the right path for enterprise automation.
- Mahesh Anantapanagamanam — CEO and founder of QBotica. Pioneered automation-as-a-service / RPaaS in 2017-18, before forward-deployed engineering became a mainstream consulting model.
- Dominic Barola — QBotica, host.
The core argument: legacy automation has stalled
- RPA delivered initial value, then plateaued under maintenance cost, broken bots, and developer dependency.
- Most generative AI tools push the maintenance problem in a different direction — opacity, hallucinations, and audit gaps make them risky for back office and finance.
- The next phase needs LLM-powered understanding wrapped in a deterministic interpreter — so the AI can be creative inside well-defined boundaries while the runtime stays auditable.
How Kognitos and QBotica fit together
- Kognitos: English-as-code platform with conversational exception handling. Business users describe processes in English; the platform executes them deterministically and surfaces exceptions in English for the user to resolve.
- QBotica: automation-as-a-service delivery model where clients pay for outcomes as they're delivered — not license bulk-buys or T&M hours up front. Mahesh notes this aligns with OpenAI's recent move to forward-deployed engineers inside client teams.
- Joint promise: clients buy results (hours saved, errors avoided, cycle time reduced) rather than tools-plus-hope.
Where AI changes the ROI math
Both speakers come back to the same point: the highest-ROI use cases were always the ones legacy RPA couldn't touch — document-heavy, exception-prone, dynamic processes. Those are exactly where hallucination-free AI automation now becomes economical, because handling the long tail no longer requires a developer for every edge case.
Questions answered in this video
Who are the speakers and what does each company do?
Binny Gill (founder/CEO, Kognitos — English-as-code automation platform) and Mahesh Anantapanagamanam (CEO, QBotica — automation-as-a-service delivery firm that pioneered RPaaS in 2017-18). Dominic Barola from QBotica hosts.
What does “hallucination-free AI automation” mean in this context?
It refers to Kognitos's architecture, which uses LLMs for understanding and creativity but executes the resulting program on a deterministic English-as-code runtime. The runtime doesn't guess — it does exactly what the human-readable program says — so back-office decisions remain auditable and predictable.
What's the QBotica delivery model?
Automation-as-a-service / RPaaS — clients pay for outcomes as they're delivered, not for license bulk-buys or T&M hours up front. Mahesh notes this aligns with OpenAI's move to forward-deployed engineers embedded inside client teams. The customer pays for results once they materialise, not on hope.
Which use cases does the webinar say AI now makes economical for the first time?
Document-heavy, exception-prone, dynamic processes — the long-tail finance, customer-service, and back-office workflows that legacy RPA couldn't touch because every edge case required a developer. With hallucination-free AI automation, the long tail stops being a developer problem.
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