Cognous helps enterprises move from AI experimentation to governed AI deployment. We focus on the infrastructure, artifacts, and operating discipline required to make AI-agent behavior declarable, controllable, replayable, and reviewable.
Cognous works on the governance layer around AI deployment — especially where AI systems and agents begin to interact with tools, workflows, data, APIs, and business processes. Our focus is the practical work that makes agent behavior something an enterprise can declare, control, reconstruct, and review.
Enterprises are moving from chatbots and copilots toward agents and AI-enabled workflows that can affect business systems. This creates governance questions that ordinary prompts, logs, dashboards, and policy documents do not fully answer.
AI governance is moving from output review to action governance.
Organizations need to know what AI systems may do, what they attempted, what was allowed or blocked, what sources they relied on, how runs can be reconstructed, and what evidence supports deployment decisions.
Ex-AWS Market Intelligence — cross-cloud taxonomy, semantic validation, internal AI tooling. Prior: Lenovo, HP. Owns architecture, product, patents, and strategy.
LinkedInEx-HP VP, Corporate Strategy & Incubation. Built enterprise strategy and decision systems supporting a $100B+ technology portfolio. Leads commercialization, partnerships, fundraising, and enterprise operations.
LinkedInSenior backend engineer; prior Nisum, Mercor, InStride, Dave. Columbia JD. Leads engineering execution, backend architecture, benchmarking, and evaluation.
LinkedInCognous does not replace legal, compliance, audit, or security functions. It helps create the structured artifacts and operating workflows those functions can review.
Why Cognous exists, what it builds, and the horizon it builds on — in the founder's own words.
Read the letterWe do not chase trends, markets, or narratives. We build the substrate that makes intelligence safe, legible, and interoperable across institutions, cultures, and time.
Governed AI deployment requires records, not recollection.
Agent governance must operate at the action layer, not only the model-output layer.
Blocked actions are evidence that controls operated.
Replayability should be designed before incidents, not reconstructed afterward.
Business reviewers need evidence packages, not raw traces.
Open reference artifacts can accelerate trust, interoperability, and adoption.
ODES, the Open Decision Evidence Standard, is a separate proposed open, vendor-neutral public standard for portable decision evidence in AI-mediated and cross-boundary decisions. Cognous Open Control Stack is not ODES and does not define ODES conformance. Cognous may publish or support materials related to ODES separately, but the Open Control Stack remains a distinct open-source reference initiative for governed AI-agent workflows.
If you are evaluating governed AI-agent deployment, agent governance infrastructure, or deployment evidence workflows, contact Cognous.