Tahu gives you the evidence to decide how the work gets done: a person, an AI tool, or an AI agent, for every task, and the governance to run those decisions with confidence.
HUMAN + AI
PERFORMANCE OS
The future of work is here. AI tools are live, agents are running, and decisions are being made faster than ever and yet most enterprises are managing this new reality with org charts, job descriptions, and performance systems designed for a world that no longer exists. The gap between where work is and how organizations are actually running it is not a technology problem. It is an operating-model problem.
Tahu closes that gap. We don't take the decision out of human hands, we put better evidence into them. For every task, Tahu provides a Human+AI (HAI) matrix: who or what is best positioned to do the work, in what teaming mode, and at what cost, quality, risk, and governance trade-off. You decide what makes sense for the organization. Tahu makes the decision visible, defensible, and repeatable.
Made task by task and revisited as the work changes, those decisions compound. The right people and the right AI, matched deliberately rather than by default, produce more organizational intelligence together than either could alone. That compounding is what it means to run on intelligence.
HUMAN + AI
PERFORMANCE OS
Tahu is a Human+AI Performance Operating System. It gives enterprises the architecture to orchestrate work across humans, AI tools, and AI agents with precision; matching each task to the right capability, surfacing the right teaming mode, and embedding governance directly into how work flows.
Built on process-aware telemetry and quality-adjusted throughput logic, Tahu doesn't just track what AI does. It shows you where AI belongs, at what level of autonomy, with what human oversight, at what moment and then enforces the policies your leaders set. The result is measurable: higher-quality output, bounded risk, and a workforce genuinely qualified to lead in an AI-augmented environment, not just exposed to it.
At the core is the Human+AI matrix. Every performer: human, tool, or agent, is measured on one comparable framework and carries a unified record across six dimensions: specification, capability, teaming mode, organizational context, governance, and economic routing. The organizational context dimension is what gives an agent the contextual and cultural intelligence to act like it belongs to your organization. Four teaming modes - Assist, Review-HITL, Co-Create, and Autonomous - describe exactly how people and AI share each task, matched to its risk and uncertainty.
Tahu is built on broad portfolio of patent filings spanning the full human-AI performance lifecycle, and is aligned to the EU AI Act, the NIST AI Risk Management Framework, and ISO 42001.
The future of work is here. Tahu is how you run it.
HUMAN + AI
PERFORMANCE OS
A Human+AI performance platform only works if two things are true at once: the system has to route and govern work with precision, and the people around it have to trust it enough to use it. Tahu's founders have spent decades on opposite halves of that equation: one designing the human conditions that make them stick, the other building the decision systems.
Dr. Carly Cooper designs the human side of the equation. An organizational psychologist and scholar-practitioner, she has spent decades building the cultures, structures, and conditions that determine whether people actually adopt new technology, or quietly route around it.
At Tahu, she leads the human architecture: the trust, psychological safety, and change design that turn a governance engine into something teams will use and believe in. She is also a Fulbright Specialist and an Adjunct Professor at Brown University and the University of Southern California, where she teaches leading strategic change, leadership, organizational culture and the future of HR.
Her practitioner record spans the enterprises where this work is hardest. She led culture and transformation initiatives at SAP, Infosys, and Barclays, and was the eighth employee and a leadership-team member at the AI company Vianai, where she built the company's culture and prototyped generative-AI tools for employee self-service. Her doctoral research, published in 2019, examined and recommended how large enterprises can prepare both their workplace (culture) and their workforce (people) for the impact of AI, concluding that the job to be done is a function of people and technology.
Paul Lee builds the systems that decide how work gets done. Trained as an operations-research engineer at Stanford, he has spent decades turning complex data into decisions leaders can act on, and increasingly into AI systems that can act on their own.
At Tahu, he architects the performance engine: the telemetry that measures work, the logic that routes each task to the right performer (human, tool, or agent), and the governance that keeps escalation and oversight intact as autonomy increases. He has led the development of AI-powered decision-support and performance-analytics products at Ecuiti.
That work rests on a rare through-line from deep engineering to enterprise strategy. Paul began at AT&T Bell Laboratories commercializing new technology out of R&D, advised venture-backed companies on eBusiness strategy at Scient, served as a Vice President at Gartner, and was a Partner at Keystone Strategy, where he acted as Microsoft's chief market analyst on global competition matters. Across every role, his specialty has been the same: making large-scale, high-stakes decisions legible, measurable, and accountable.
