The intelligence-infrastructure layer for multi-agent AI
CODAMERE

Built for institutions that can't afford to forget.

Every multi-agent AI system has the same fatal flaw — it forgets. Each session starts from zero. No learning compounds. No coordination holds. Codamere built the layer underneath: a persistent memory graph, a resident agent squad, edge compute, and the governance fabric that lets regulated operators deploy AI they can actually defend.

335K+ graph nodes · 250 virtual teammates · 99.3% embedding coverage · 6 weeks to first terminal
The bet

The closest investment-grade comparable to Codamere isn't an AI company.
It's infrastructure.

The $3.4B that flooded into AI agent frameworks funded the apps. Nobody built the memory and coordination layer underneath. Each agent demo forgets at session end. Each chatbot is a stranger to itself. No learning compounds. No coordination holds across machines, models, or quarters.

Codamere built that layer. A persistent memory graph that survives the model. A daemon mesh that holds coordination across machines. A governance fabric that lets regulated industries deploy AI they can actually audit. Live. Deployed. With customers paying for it and asking for exit participation in their service contracts.

This is the shape of infrastructure companies, not application companies. We are building the platform underneath an era — not the demo on top of it.

Shopify
2006
Built the store infrastructure. Merchants owned the customer relationships.
Stripe
2011
Built the payment infrastructure. Developers owned the product.
Palantir
2005
Built the intelligence infrastructure. Clients owned the decisions.
Codamere
Now
Builds the memory + coordination layer. Operators own the intelligence.
The Stack

Six layers. One coherent system.

Most AI vendors sell one of these and call it a product. Codamere built them as a single fabric — because intelligence that isn't persistent, coordinated, governed, and grounded is theatre.

01 / MESH
MERIDIAN mesh & harness
A NATS-coordinated daemon network where every agent is a citizen with a name, a job, and a record. Specialised stations — coherence, research, deal flow, legal, ops — coordinate through a shared event bus and a shared graph. Not one big model. A mesh.
02 / MEMORY
Multi-layered persistent memory
A Neo4j-backed graph that holds every fact, decision, observation, and source. 335K+ nodes, 38K Memory, 9.8K Concepts, 2.5K Research, 99.3% embedding coverage. The longer it runs, the more useful it becomes — and the harder it is to replace.
03 / SQUAD
Resident agent squad
250 virtual teammates on call — research analysts, deal directors, librarians, counsel, ops engineers, OSINT investigators. Each one is an addressable persona with memory of prior work and a defined zone of authority. They show up to the meeting already briefed.
04 / EDGE
Edge compute & data metro
Compute and storage close to where the data lives, with a tenanted data metro architecture per client. Local embedding, local inference where it matters, tunneled access where it doesn't. Your infrastructure. Your keys. Your jurisdiction.
05 / GOVERNANCE
Auditable to the action
Every memory write carries a daemon, a source, a confidence, and a chain. Every claim has provenance. Two-phase consent on structural changes. If a regulator asks why — the answer is already in the graph, not in someone's head.
06 / R&D
Foundational orchestration breakthroughs
Coherence gating. Identity locks across distributed sessions. Anti-drift sentinels. Phase checkpoints that survive context compaction. The hard parts of multi-agent systems that the demos never have to solve — because the demos don't run for a year.
The wedge

What bigger firms take six months to ship, we deliver in six weeks.

We don't sell a generic platform. We deliver a fit-for-purpose terminal — your stations, your data, your decisions — running in production inside six weeks of engagement start. The compression is the moat. It comes from the stack underneath, not heroic effort.

Every engagement runs on the same operating discipline: humans remain the interface; the system carries the work. Pricing is anchored to outcomes, not seats. We don't take on every project — the partner has to be the person who actually owns the operation.

  • 01
    Fit-for-purpose terminals
    Not a generic SaaS. Your domain, your decisions, your stations — composed from a shared spine. No two terminals look alike.
  • 02
    Six weeks to production
    From kickoff to a terminal an operator uses daily. The compounding moat is the stack — we don't rebuild the platform each engagement.
  • 03
    Humans as the interface
    Your team stays in the seat. The system carries the load underneath. Nothing ships to a counterparty without a named owner.
  • 04
    Pay for results
    Pricing is anchored to outcomes — terminals delivered, throughput improved, decisions accelerated — not to seats or token volume.
  • 05
    Tested where the stakes are real
    Deployed inside regulated capital markets, professional-services boutiques, and operating partnerships. Not a research demo. A live system, on the record.
335K+
Graph nodes in production
11
Daemons running 24/7
250
Virtual teammates on call
99.3%
Embedding coverage
6 wk
From kickoff to a live terminal

"Treat the memory graph as the asset, not the model. Build everything else around protecting it."

— Codamere field doctrine
Built on the spine

One platform. Four operators.

Each Codamere product is a vertical operator running on the MERIDIAN spine — one memory graph, one event bus, one operating discipline. Pick a wedge or compose them.

M
Meridian
The platform — daemon mesh + memory graph

The spine underneath every Codamere terminal. A network of specialised daemons sharing a persistent graph, an event bus, and a strict discipline about what AI is allowed to claim.

sensei atlas delphi forge talon avery
See the platform →
T
Codamere Terminal
Vertical — fit-for-purpose operating system

A composed terminal for a specific operator — capital programs, agency operations, professional services. Stations are agents; the operator decides which ones run. Six weeks to production.

$ terminal capital --program=fund-iii --quarter=Q3
12 LPs surfaced · 4 active threads
IC memo: draft ready
compliance: 2 disclosures flagged
station.legal routed 1 escalation
$ approve --with-evidence
See the terminal →
V
Agent Vox
Voice — live coaching in regulated conversations

Listens to live calls and works the operator in real time. Tracks where the conversation should go next, surfaces the right move before the counterparty can disengage, writes every call back to the graph with sources.

See Agent Vox →
B
Boardroom
Voice — autonomous qualification calls

Takes meetings on your behalf — qualification calls, intake interviews, follow-ups. Reads from your memory graph, talks like the firm, books time, and writes the meeting back to where it belongs.

10:42 caller "Tell me what you actually do."
10:42 boardroom routing → discovery script v3
10:43 graph recalled 2 prior touches
10:46 action booked Wed 3pm
10:47 handoff → avery (deal director)
See Boardroom →
Engagement model

How working with Codamere actually goes.

We don't sell pilots. We deliver terminals. Four stages, six weeks total, every artefact on the record from day one.

For whom

Codamere is not for everybody.

We're built for institutional operators in finance and regulated markets — places where an AI claim has to be defensible, traceable, and on the record.

Fit

  • Capital programs, funds, family offices, allocators — where decisions are governed and evidence chains matter
  • Professional-services boutiques (legal, accounting, advisory) running repetitive, high-stakes knowledge workflows
  • Operating partnerships in regulated industries that need AI on the record, not in the chat window
  • Founders and operators who already own the operation and want to compress, not replace, their team
  • Buyers who care about governance, provenance, and a defensible audit trail more than demo dazzle

Not fit

  • Teams looking for a chatbot — there are cheaper options that don't pretend to be infrastructure
  • Engagements where the buyer doesn't own the operation and can't make decisions in the room
  • Projects optimising for "AI feature parity" with a slide deck rather than operating outcomes
  • Industries where governance and provenance are nice-to-haves rather than the price of admission
  • Pilots without an explicit production path — we don't take on demo-ware engagements
Bring us a real operating problem

A first conversation. Thirty minutes, no deck.

We respond in one business day. If we're not the right fit, we'll say so on the call and point you somewhere better. If we are — the next step is a discovery week, not a contract.