Your company already knows this. It just can't remember.
Cogniseam turns everything your organization knows into governed, cited memory your people and your AI can trust.
“Nobody knows which document is current.”
“Employees ask the same questions over and over.”
“The AI gives different answers depending on the prompt.”
“Knowledge disappears when experienced people leave.”
“Two policies say two different things.”
“Teams rebuild work that already existed.”
A company that can't remember pays for it every day.
The knowledge already exists. It's the remembering that's broken — and the cost compounds quietly, in four places.
People search for what the company already knew — again and again, in a different tool each time.
Choices made on stale or unverifiable information, with total confidence and no citation.
When someone leaves, the context behind a decision leaves with them. The company forgets.
Agents you can't trust to be correct, access-scoped, or auditable never make it past review.
You've tried to fix this. Here's where each approach stops.
Finds documents. Doesn't understand them, can't answer, and has no memory of what changed.
Depend on humans to write and update. Go stale the moment reality moves; no access logic at answer time.
Retrieve chunks and hope. Access is bolted on after, provenance is a guess, stale chunks resurface.
Answer, then stop. No governed action, no approval gate, no audit of what they did or why.
An operating system for your company's memory.
What a company needs isn't another search box — it's enterprise memory: one governed place where knowledge is remembered, cited, and safe to act on. Cogniseam is that system — an Enterprise Memory Operating System, built on a governed memory engine — turning what every tool already holds into outcomes.
- Enterprise SystemsSlack · Microsoft 365 · Drive · ERP
- Connectorssync · live capture · CDC
- Normalizationone idempotent pipeline
- Knowledge Extractionfacts · entities · policies · skills
- Enterprise Memoryretrieval · history · supersession
- Knowledge Graphentities · relationships
- GovernanceRBAC · audit · approvals · encryption
- Executionanswers · skills · workflows · agents · API
- Business Outcomesfaster decisions · recovered revenue · provable compliance
Every page zooms into one stage of this flow — see the architecture →
Knowledge changes. Memory keeps the history.
A fact is created, updated, and superseded — the old value retained, never silently overwritten. When an agent asks, it gets the current answer, cited, with the reasoning on the record.
- 2023 · Q1Policy created
Refund authority ≤ $2,000
source · Finance Policy 3.1 - 2024 · Q3Policy updated
Raised to ≤ $5,000
source · Finance Policy 3.2 - 2024 · Q3Fact superseded
≤ $2,000→≤ $5,000 (current)
The old value is retired but retained — history stays queryable.
history kept · not deleted - todayAn agent retrieves the newest version
It answers with the current figure only — never the stale one.
cited · Finance Policy §3.2 · visible to: Finance - todayThe audit records why
The decision and its full chain of custody are written to the ledger.
ledger · #48291 · answered from current policy
Watch a question become a governed answer.
A plain-language question flows through retrieval, evidence, governance, a human approval gate, and an audit record — to a cited answer no single document contained.
- Question
- Retrieval
- Evidence
- Governance
- Approval
- Audit
- Answer
A person or an AI agent asks in plain language — no query syntax, no dashboards.
Governed by design — not bolted on.
Access control at retrieval
Every agent and every person only ever sees what they're cleared for. Admins don't bypass it.
Every answer is cited
Grounded in your sources with inline citations — or it says it doesn't know, instead of guessing.
Works with your models
Anthropic, OpenAI, and Gemini behind one interface — switchable at runtime, bring your own key.
Disconnected knowledge → enterprise memory → governed intelligence → business outcomes
Give your company a memory it can trust.
Book a walkthrough with our team, or start building on the Agent API today. Either way, you keep your models, your stack, and a full audit trail of everything your AI does.