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Memory and judgment for teams and their agents
Your agent will re-solve a problem your teammate already fixed, the wrong way, because nothing told it that happened. Cognition hands it the fixes, decisions, and judgment your team already earned, before it acts.
Built by brains from
In the field
~200 sessions per physician over 30 days · Mayo Clinic and Roswell Park cohort · internally reported
“Cognition lets me bring my vision for cancer risk modeling to life almost exactly as I see it. There are countless moving parts: the market, our ICP, the team, the way we reason through decisions. Cognition pulls all of it into one place, keeps everything aligned, and surfaces connections I would have missed. It feels like I’m working with myself.”
Dr. Aneel Paulus · Oncology · Mayo Clinic
17 minutes19seconds
Context recovery for a new agent
A fresh agent picks up where the last one stopped instead of re-reading the project.
6.5 hours3.8minutes
Reconstructing a past clinical decision
Why a call was made, who made it, and what it rested on.
289corrections
Clinician corrections absorbed
Each one became judgment the next agent inherits, without storing a clinical record.
8.1%0.9%
Unsupported readiness claims
Consequential claims are bound to evidence and a human approval before they ship.
Measured across clinical deployments. Internally reported.
Nothing enters the brain without an explicit human yes. Every entry keeps its author, its reasoning, and the context it applies to.
Each use reports back whether it helped. Trusted judgment strengthens; one-offs decay before they can mislead the next agent.
Talk to it in plain English. Confirmation-required skills wait for a person before they fire.
Why Cognition is different
Cognition treats work as a learning signal. Skills carry freshness and outcome history, so stale guidance asks first instead of misleading the next agent.
// spectral retention: decay from the graph Laplacian export function retrievability( node: SkillNode, now = Date.now(),): number { const S = 1 / spectralGap(node.L) // S = 1/λ₁(L) const dt = (now - node.reviewedAt) / DAY return Math.exp(-(dt / S) ** node.beta)} // weakest layer bottlenecks the whole manifoldconst spectralGap = (L: Laplacian) => Math.min(...L.layers.map(eigGap))// spectral retention: decay from the graph Laplacian export function retrievability( node: SkillNode, now = Date.now(),): number { const S = 1 / spectralGap(node.L) // S = 1/λ₁(L) const dt = (now - node.reviewedAt) / DAY return Math.exp(-(dt / S) ** node.beta)} // weakest layer bottlenecks the whole manifoldconst spectralGap = (L: Laplacian) => Math.min(...L.layers.map(eigGap))Prompts, files, tool calls, decisions, and outcomes become typed learning events.
Deployed workflow by workflow — each one captured from the person who solved it, approved by a human, and retrieved only when the context actually matches.
The whole idea
Install in about two minutes, keep your keys revocable, and let the first approved skill start compounding.
$ curl -fsSL https://www.cognitionus.com/api/install/codex | COGNITION_KEY=cog_me_xxx bash
