Cognisee builds cognitive infrastructure for agentic and physical AI by turning tacit human expertise—expert judgment, embodied skill, and institutional memory—into systems that enable machines to reason and act in high-stakes scenarios. The company is developing three core primitives: Wisdom Vaults, Tacit Reasoners, and Second Brain Architectures, which together form what it calls Artificial Collective Intelligence.
Funding
Funding not disclosed
Founders
Product
Problem
Current AI systems learn primarily from recorded data such as text, labels, demonstrations, and logs, missing the most valuable knowledge that exists outside datasets. This knowledge lives in expert judgment, embodied skill, institutional memory, and local context—especially in ambiguous, high-stakes situations where decisions carry significant consequences.
Solution
Cognisee is building the missing cognitive layer for AI by surfacing tacit human expertise, structuring it, and making it usable by humans, agents, machines, and institutions. The company is developing three core primitives: Wisdom Vaults as sovereign stores of tacit expertise and institutional memory, Tacit Reasoners that apply this knowledge, and Second Brain Architectures that enable human-AI systems to learn, reason, and improve together over time. Together, these capabilities form Artificial Collective Intelligence—distributed human-AI systems that compound knowledge across people, tools, agents, machines, and time. This approach equips AI with the contextual judgment needed to operate reliably in high-stakes domains.
Target Audience
Cognisee targets organizations deploying agentic and physical AI systems in high-stakes environments—such as industrial operations, healthcare, defense, and critical infrastructure—where expert judgment and institutional knowledge are essential for safe and effective decision-making.
Features
- Wisdom Vaults designed as sovereign, structured repositories for expert knowledge, context, and institutional memory
- Tacit Reasoners that operationalize unstructured expertise into reasoning capabilities for AI agents
- Second Brain Architectures enabling collaborative learning loops between human experts and AI systems
- Focus on high-stakes scenarios where ambiguous conditions require adaptive judgment beyond pattern-matching
- Infrastructure positioned at the cognitive layer, complementing data-centric AI stacks with expertise-driven knowledge