Yunt

Companies facing growing caseloads hit a wall with manual processes that scale linearly. Hiring more people is slow and expensive, and when a senior employee leaves they take undocumented know-how with them. Generic software forces companies to adapt their workflows to the tool, while subscription AI chatbots converse and make mistakes with no one accountable for the outcome. The text frames this as a gap between scaling with people and scaling with technology, where no option gives a trained standard, human sign-off, and accountability at once.

Yunt creates 'digital collaborators' (Yunts): AI agents assigned a specific job role, built from a manual written with the client's best senior employee using HR tools like competency dictionaries and behavior profiles. Each Yunt works inside the company's existing tools and channels (email, WhatsApp, ERP) without requiring a new platform, reports to a human boss who approves significant actions, and logs every action in a 'glassbox' showing what it did, why, and at what cost. A traffic-light system cross-checks the agent's claims against its action log, flagging unsupported statements in yellow and blocking unsupported ones in red to catch fabricated information before it ships. Yunt is model-agnostic, selecting whichever underlying AI model performs best per role, and each deployment includes a 'forward deployed engineer' who learns the client's actual workflow, integrates the Yunt into company systems, and stays on to maintain and adjust it.

The text argues that AI models already do professional-quality office work; what's missing is that they know the company's specific way of working, that a human signs off on what matters, and that someone is accountable when something goes wrong.