BNRY

Artificial Neural Intelligent Mapping Architecture

ANIMA

A neural map of everything an organization knows — surfacing where its ideas converge, and what to do about it.

Beta

ANIMA is in active beta. It maps and connects an organization's own corpus; it proposes pathways and action, and a person decides. Nothing it surfaces carries authority on its own.

The challenge

The problem underneath.

An organization's thinking is scattered across documents, threads, decks, meetings and people. The overlaps are invisible, so the same problem is solved three times in three verticals and the connection that would have mattered is never made. Nothing is lost, exactly. It is just unreachable.

The system

How it is structured.

ANIMA holds the whole corpus as a connected graph and reads the graph rather than the documents. It traces pathways between distant nodes, detects where separate verticals are converging on the same problem, and resolves what it finds into action rather than search results. A second brain that remembers structurally — institutional memory that compounds instead of dispersing when someone leaves.

How ANIMA maps an organization Five domains an organization keeps knowledge in — operations, programs, finance, research and people — each drawn as a cluster of connected nodes. Seven highlighted pathways cross between different clusters, representing the connections ANIMA surfaces: places where separate parts of the organization are working on the same problem without either one being positioned to see the other. OPERATIONSPROGRAMSFINANCERESEARCHPEOPLE
Knowledge already held, organised by domain Pathways ANIMA surfaces across domains

Scope

The territory this covers.

Scope

  • Knowledge graph
  • Cross-vertical mapping
  • Overlap detection
  • Pathway discovery
  • Action synthesis
  • Institutional memory

Scope is the territory this covers. The status above marks where it stands on that track today.

Market position

The category this system operates in.

  • $3.5BEnterprise knowledge-graph market, 2026
  • 21.3%CAGR through 2033
  • $21.9BSame market, 2035

Sources: Grand View Research · SNS Insider, Aug 2026

The story

What we found, and what we made of it.

  1. The problem

    An organization's thinking ends up scattered across documents, threads, decks and people. Nothing is lost, exactly — it is unreachable. So the same problem gets solved three times in three verticals, and the connection that would have mattered is never made because no one was positioned to see both ends of it.

  2. What we saw

    Search was the wrong instrument. Search answers the question you already knew to ask, and the expensive gaps are the ones you did not. What was missing was not retrieval. It was adjacency — a structure that holds the whole corpus at once and can see where two distant parts of it are converging.

  3. What we built

    ANIMA holds the corpus as a connected graph and reads the graph rather than the documents. It traces pathways between distant nodes, detects where separate verticals are arriving at the same problem, and resolves what it finds into action items rather than results. Institutional memory that compounds instead of dispersing when someone leaves.

Who it serves

And what it is for.

Leadership teams, multi-venture operators, research groups, and any organization whose knowledge outgrew its filing.

The organization stops re-deriving what it already knew, and starts acting on the connections it could not see.

Discuss ANIMA.

Tell us about your setting and what you are trying to change. We will be straight with you about where this system currently is.

Request a consultation

Explore YFSExplore AkiliExplore VertexExplore Executive OS