Cognition provides a collaborative knowledge base that captures, approves, and organizes coding skills and workflows for software teams and AI coding assistants. Its forgetting graph prioritizes relevant knowledge and schedules reviews, ensuring consistent code practices and streamlined onboarding.
Funding
$1.6B raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+5Founders
Product
Problem
Coding teams often rely on informal, undocumented knowledge transfer, leading to duplicated effort, inconsistent code practices, and difficulty onboarding new developers or AI coding agents.
Solution
Cognition offers a collaborative knowledge base that functions as a shared “brain” for coding agents within an organization. Teams create a group‑code environment where each member’s coding agent can observe real work contexts, capture approved coding skills, and store the source and rationale behind each skill. A forgetting graph prioritizes skill retrieval and timing of reviews, ensuring that the most relevant knowledge is surfaced when needed. The platform automates the drafting of reusable skills, requires explicit human approval before they are saved, and continuously updates the knowledge graph based on outcomes, reducing manual knowledge transfer and improving code maintenance consistency.
Target Audience
Primary users are software development teams and organizations that employ AI coding assistants and need a structured, auditable repository of best‑practice code snippets and workflows.
Features
- Group‑code setup that lets a single initiator create a shared brain and invite teammates and their agents to join
- Automatic capture of work artifacts (files, commands, decisions, reflections) to provide context for each skill
- Skill drafting by the Coding Language Operator (CLO) with explicit human approval workflow before persistence
- Forgetting graph that scores skills for retrieval and schedules review nudges based on decay rather than arbitrary timing
- Provenance tracking that records who taught each skill and the justification for its effectiveness
- Continuous update loop where execution outcomes feed back into the graph to sharpen future suggestions