Enterprise AI tools can spin up a prototype in an hour. Getting that prototype to production with the accuracy, security, and scale a real business needs still takes months for most companies. Inbenta says its new Encore platform closes that gap in days.
Merlin Bise, CTO at Inbenta, returns to VUX World to walk through how Encore builds production-grade AI agents on the fly when a customer deploys a use case. The platform ingests content from websites, documents, recordings and connected systems like SharePoint, then combines large language models with Inbenta’s proprietary NLP, customer-specific lexicons and real-time intent generation to deliver near-zero hallucination rates.
The hallucination numbers from raw models remain striking. We discuss a report that shows hallucination rates across different LLMs, including those from companies such as OpenAI, Google, and xAI. Inbenta’s approach constrains the model to verified content and context, then layers intent-based NLP on top. In one customer test of 200 questions, they found a single hallucination, caused by a query that fell outside the content boundaries.
We also discuss the broader trajectory of enterprise AI. Most deployments today focus on replacing existing activities or functions. The bigger opportunity lies in using AI to imagine entirely new kinds of value. Merlin predicts that hyper-automation, which combines agentic intelligence with robotic process automation, will be the defining shift in the next 12 months.
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