The architecture, the brains we build with it, and the discipline that keeps it true.
The architecture has two dimensions. The four blocks describe how the brain perceives, models, reasons and answers. The three knowledge layers describe what it knows and why you can trust it. Together they are one substrate.
Atomic agents that perceive the work and emit clean signal, with no dashboards and no manual reporting. The ones we run in production:
Presence: the real-time state of the team, deduced by crossing signals, not by asking.
Activity: what each person is doing, tied to clients, projects and work types, without anyone labeling it.
Communications: the day-to-day with clients and inside the team, captured without forwarding or uploading, normalized into a queryable timeline.
Sources-of-truth ingestion: parsers and LLM-assisted extractors that project documents, code, policies, tickets and transcripts into the graph, idempotently, with provenance on every claim.
Company world model, live: who knows what, what decisions were made, what is happening now.
Customer world model, live: a real understanding per customer or account, built from how you actually work with them, not from CRM fields.
Institutional knowledge, executable: the three layers below, cross-linked into the same graph.
Composes the capabilities over the world model to solve real problems the moment they happen: assign work to the right person, onboard a new joiner with sourced answers, flag an account going at risk, surface the precedent before a decision repeats a known mistake, propose a successor when someone rotates off.
A conversational interface for the humans on the edge.
MCP-first, so your own agents query the company directly, with citations. Your company stops being people plus a portal and becomes a queryable organism.
Generated views, always in sync: executive maps, narratives, digests, per-audience reports from one signal.
The purpose of the system, the principles that uphold it, the core domain concepts, the playbook practitioners execute, and the history of tuning: every improvement as problem, action, result. The layer executives and new hires read first.
Processes and phases with budgets and objectives, components and who runs what, data flow step by step, feature flags and what each toggles, environments made explicit, so nobody mistakes a prototype for a live control.
Every rule with the real case that motivated it, every test and which rule it anchors (so deleting the rule breaks the build), golden cases that freeze correct outcomes, a version-by-version changelog, findings traced from who raised them to the version that closed them.
The cross-links are the product: a principle in layer 1 is anchored by rules in layer 3 and enforced by components in layer 2, all refreshed by the live signal from the capture agents. Ask "which of our principles have no enforcement" or "who is working on the thing this rule protects" and the brain answers structurally.
The substrate is constant. What changes is the domain it models and the questions it answers. Several of these we operate in production today.
The brain a product team builds and maintains its product with. It models the product's purpose and methodology, its full architecture, and its complete quality layer. In production behind a live AI interviewing product: it exposed, by query and not by luck, an entire product stage without regression tests, a live methodology contradiction between documents, and a validated control everyone believed was running in production.
Every repo, service, endpoint and dependency, mined from real code and infrastructure, refreshed with each commit. Answers impact and blast radius, ownership and bus factor, security surface, where risk concentrates, and what to retest after a change. Behind our AI software delivery practice, where it also generates each project's engineering constitution from real patterns.
People, teams, interventions, initiatives, evaluations and incident history across an organization, fed by automated pipelines on schedule. Answers what a person was asked to do and what happened, which incidents repeat, which interventions worked. In production organization-wide, used daily by leadership, with automated hygiene after every ingest.
Decisions, standing instructions, per-person communication styles and per-topic knowledge, with vector recall, injected automatically into every AI work session by relevance. Industry research attributes most enterprise AI failures to context and memory loss, not the model. This brain is the fix: the AI never re-asks answered questions and applies instructions given weeks earlier in other contexts.
Every policy with the reasoning and incident that motivated it, what enforces it, the audit trail of changes, and the map between what is written and what is actually live. Answers which controls are real versus documented, what evidence supports each claim, and what changed between audits and why. Where it bites: regulated industries where "show me the evidence" is a recurring event.
Per-account institutional knowledge: what was promised, decided, tried and learned across the whole relationship, from communications, tickets, contracts and meetings, kept live by the capture agents. Where it bites: agencies and services firms with rotation risk, and SaaS companies where handovers lose the context churn post-mortems later rediscover.
The knowledge that walks out the door, captured, structured and verified before it does: an expert's reasoning, a retiring cohort's know-how, an acquired company's memory. Where it bites: key-person risk, retirement waves, M&A integration, and fast-scaling teams where onboarding consumes senior time.
Every brain is the same contract: built from your real sources of truth, kept current by live signal, regenerated so it cannot rot, explainable in plain language, verified adversarially, and queryable by people and agents alike.
Most knowledge projects die in the maintenance: someone has to keep them true, so nobody does. We design that failure out. Three decisions do most of the work: the graph regenerates from sources of truth (so it cannot rot), every claim carries provenance (so it can be attacked), and every relationship reads as plain language (so humans and LLMs consume it without a translator).
We map your sources of truth and your decision pain: the questions you wish you could answer instantly, the knowledge that walks out the door, the fixes that silently regress. Output: a brain charter with the domain scoped, the schema drafted in your language, and the source inventory.
The ingestion pipeline is built against your real artifacts: documents, codebases, prompts, configuration, CRM records, transcripts, email threads, tickets, reports. Deterministic parsers plus LLM-assisted extraction, idempotent by design. First full projection loaded and queryable, every node and edge citing its source.
We attack the brain before you rely on it. Multi-agent audit workflows verify the graph claim by claim against the sources. In production these audits caught wrong-direction relationships, duplicate identities, cross-contaminated records, and rules that claimed test coverage they did not have. Every finding becomes a pipeline fix, so the same error cannot recur.
Every relationship gets its plain-language sentence. Acceptance test: a business person who does not know the technology reads the graph and understands it. So does an LLM.
From the same graph, always in sync: executive maps, narratives, digests, dashboards. And your decision queries codified: the questions that used to take a week of archaeology now take seconds.
The capture agents keep the operating state current. The brain connects to your AI agents (MCP or API) and injects relevant context automatically. Rebuilds run on every source change or on schedule, with the verification harness as gatekeeper. The brain stays true because staying true is automated.
Powered by the Neocortex. The intelligence layer that ships with every brain we build. It arrives knowing the job and keeps getting smarter with every deployment.
Meet the Neocortex →Book a working session. Bring the three questions you most wish your company could answer instantly, and we will stand up a slice of your real operating picture on your real tools. Scope: defined with you in the working session.