# AIORG Knowledge

> One curated knowledge base for every agent

Learn once. Every agent knows.. Facts about your systems, services, and decisions are extracted, curated, and verified once, then served to every agent in the organization so they all act on the same truth.

## The problem: Every agent starts from zero

- What your company knows lives in heads, wikis, and diagrams that were true last spring.
- Every AI session re-learns your architecture, or worse, hallucinates it.
- Ask two agents the same question and you get two different answers. There is no single truth.

## The AI-Native way: In an AI-Native org, the organization remembers

- Facts are learned once: scanners read your repos and clusters, a curator verifies what they find.
- One org brain holds entities, relationships, and a live service registry, sourced and current.
- Every agent gets the same verified facts at the moment of use, via MCP and APIs.

## An organization that remembers

**You multiplied the workers, not the knowledge.** AI gave your organization more hands than it has ever had — and every one of them starts ignorant. A language model is stateless: each session rebuilds its picture of your company from scratch, paid for in tokens, in time, and in the mistakes it makes while guessing. Multiply that re-learning tax across every agent and every session, and your org runs on as many versions of the truth as it has context windows.

**Documentation rots; systems do not lie.** Wikis go stale the day after they are written — the diagram from last spring, the port that changed, the service deprecated quietly on a Friday. Your repositories, clusters, and manifests cannot drift from reality, because they are the reality. So that is what Knowledge reads: scanners walk the actual systems and propose facts — services, owners, dependencies, relationships — grounded in sources, not memory.

**Curation is what makes facts trustworthy.** Raw extraction produces duplicates, conflicts, and noise — the same reason raw code needs review. A curator pipeline merges and deduplicates automatically; anything contested waits for a one-click human ruling. Every surviving fact carries its sources, verification state, and freshness. Not accumulated — curated. An agent reading it knows exactly how much to trust it, and why.

**Learned once, known everywhere.** The moment a fact is verified, it belongs to the whole workforce: cloud workers and enrolled developer agents alike, served over MCP and APIs, injected into context at the moment of use. And the flow runs both ways — agents propose corrections and attest to what they observe, human-gated, so the knowledge base is fed by the very workforce that uses it.

**Knowledge compounds.** Every verified fact makes every future task slightly cheaper, faster, and safer — the derivation happens once instead of ten thousand times. A static wiki depreciates from the day it is written. An org brain fed by scanners, curators, and working agents appreciates instead: your organization gets smarter every day it runs.

## Capabilities

- **Verified facts & entities** — Facts carry sources, verification state, and freshness, so agents can trust what they read.
- **Service registry** — Repos, deployments, services, and their dependencies, deep-scanned and kept current.
- **Curator pipeline** — Automated merge, dedupe, and rewrite with human review for anything contested.
- **Briefings** — Dense, actionable summaries per entity, built for LLM context windows, readable by humans.
- **MCP & APIs** — Serve knowledge to any agent or tool through standard interfaces.
- **Agent feedback loop** — Agents can vote, attest, and propose corrections, gated by human review.

Get started: / · Portal: https://portal.aiorg.io