Atlas is the queryable graph of your objectives, decisions, designs, and ownership. Every agent reads it before it acts and writes back when it's done — so dozens of them build in parallel without drifting, duplicating, or contradicting each other.
One AI agent is easy. Twenty, running in parallel for six months, is a different problem entirely. Agents don't share memory — each session starts cold. So at scale, predictable failures compound.
Without a record of what was decided and why, every agent reopens the same architectural debate.
Two agents touch the same interface with no shared constraint, and the integration breaks.
No one can see what's already in flight, so the same story gets built twice.
Patterns established months ago are invisible to an agent that wasn't there.
Hard-won reasoning evaporates the moment a session recycles.
When something's wrong, there's no trail of who decided what, or which agent shipped it.
Wikis don't fix this — agents forget to read them. Tickets don't fix this — they track work, not truth. You need a source of truth agents query as naturally as they call any other tool.
Atlas isn't a project tracker, a wiki, or source control — it's the queryable model that links them. The operating context that makes coordination possible without shared memory. Every fact is a node; every relationship is an edge.
The persona accountable for every entity — with per-call identity and a full audit trail.
Prioritized P0/P1/P2 goals and the user-value stories that advance them.
Every architectural choice and technical design — with author, rationale, and provenance.
A registry of deployable services with dependency edges, and the tickets delivering them.
Ask Atlas "what depends on the auth service?" or "why did we choose this pattern, and who approved it?" — and the graph answers, with full content and full provenance, never a lossy summary.
Every node is a live Atlas entity. Every edge is a real relationship — an agent owns a decision, a decision constrains a service, a design cites a decision, a ticket delivers a story. This is how 28 parallel agents stay one company.
Atlas speaks the Model Context Protocol, so it's a tool surface your agents already know how to use. The loop is the same for every agent, every session.
At session start, the agent queries Atlas: active objectives, the decisions that constrain its work, the designs it must align with, and what's already in flight.
As it works, the agent records new decisions, links stories to services, and leaves a structured trail — so the next agent inherits its reasoning instead of rediscovering it.
At session end, the agent updates status, logs work events, and closes the loop. The graph is always current because keeping it current is part of doing the work.
27 MCP tools cover the full surface: search, decisions, stories, objectives, services, TDDs, tickets, the agent registry, and the link graph that ties them together.
Every entity and relationship in one navigable graph. Force, hierarchy, matrix, and radial layouts; 2D and 3D; node-level inspector.
Every architectural choice is a first-class record with author, rationale, status, and supersession history. Settle a question once.
P0/P1/P2 objectives as first-class entities. Coverage rolls up automatically from linked story status.
A registry of what runs where, with dependency edges so a change's blast radius is one query away.
Atlas returns the real artifact, not a lossy paraphrase. Agents reason on ground truth.
Subagents, skills, MCP servers, and persona charters, each with a clear owner and curator scope.
A first-class Model Context Protocol surface. Works with the agent stack you already run.
Every read and write is bearer-gated and bound to a single role; write tools validate the acting role on every call. An agent can only do what its role allows.
Field-level change tracking, per-call cryptographic agent identity, and a queryable work-event log of every agent action. Know who did what, when, and why — always.
Nothing in the model is tied to one product or vertical. Atlas governs any codebase.
Running fleets of coding agents who need them to converge, not collide.
Who need decisions to stick and architecture to hold across hundreds of autonomous sessions.
From a clever demo to a system that ships real software for months on end.
Atlas governs the real, multi-month build of a production platform — every day, in parallel.
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The 2026 thesis for AI agents isn't autonomy — it's accountability. A source of truth is only worth as much as its integrity, so Atlas is permissioned, logged, and auditable end to end, and built to fail closed.
Every read and write is bearer-gated, and each token binds to a single caller role. Write tools validate the acting role against the token's allowed roles on every call — an agent can only do what its role permits.
Curator scopes define who owns which entities. Ownership is a first-class, queryable property of the graph — enforced, not a convention agents are trusted to follow.
Per-call agent identity flows through every change, so every decision, edit, and status transition is attributable to a specific agent — not just "an automation."
Field-level change tracking on every entity. Decisions carry author, rationale, and supersession history; deletions leave a tombstone. Nothing changes silently.
Every meaningful agent action is recorded as a work event you can query by service, agent, or time — one searchable trail of who did what, when, and why across the whole fleet.
Atlas refuses to boot without its secrets and rejects placeholder credentials outright. There is no silent insecure mode.
Agent governance is the practice of giving long-lived, parallel AI development teams a shared, queryable source of truth — objectives, decisions, designs, and ownership — so they coordinate instead of conflict. Atlas is a platform for exactly that.
Those track work, store prose, or retrieve text. Atlas models the relationships between your objectives, decisions, services, and the agents that own them — and exposes that model as a tool agents call directly. It's connective tissue, not another silo.
MCP is the open standard for giving AI agents tools. Atlas ships 27 MCP tools, so your agents query and update the source of truth as naturally as they call any other tool — no scraping, no custom glue.
No. If your agents speak MCP, they can use Atlas today. The session loop — load context, work, write back — layers on top of the agents you already run.
No. Atlas is domain-agnostic by design. It was built to govern one production platform, but nothing in the model assumes a domain — it governs any codebase or org.
Both. Atlas has a full web UI — dashboards, a decision explorer, a service map, and the interactive knowledge graph — alongside the agent-facing MCP and REST surfaces.
Atlas is offered through Viradev as a product and implementation engagement. Talk to us about your agent stack and we'll show you the graph on your own context.
Tell us how you're running agents today. We'll walk you through Atlas on a live system and scope what it looks like on your codebase.
Atlas is offered through Viradev as a product and implementation engagement. Talk to us about your agent stack and we'll show you the graph on your own context.