Alexandria

AI builds faster than anyone can follow.

Alexandria makes it one picture again.

A living twin of your system, written by your AI agents and read by everyone: engineers, product managers and business owners, from business need down to hosting cost.

For engineers

Too much to read. Nowhere to find it.

Every agent session leaves plans, diffs and research behind. Reading all the code is pointless, and the rest is scattered across chats, branches and laptops.

Hard to find, hard to share, hard to build on.

For product managers

The source of truth is locked in the code.

To see how a feature spans the system, you ask an engineer or dig through code. Then the task becomes pages of text.

The developer pastes it into an agent, which researches the codebase all over again.

For business owners

Paying for AI without seeing what it buys.

AI spend grows every quarter, yet nobody can show what it delivered or where engineers still make the difference.

So budget and hiring are decided on gut feeling.

Introducing

Alexandria.

One shared picture of your system, for your whole team and its agents.

One twin

Your agents write it. Everyone reads it.

While they work, your agents describe the system in one model through MCP. Nobody draws, so nothing goes stale.

Every reader gets the view they need: use cases, domain, map, flows, data, deployment, forecast and logbook.

Same scattered pieces, now in one place.

For engineers

Each session starts where the last one ended.

Agents record designs and decisions in the twin and read them back through MCP, instead of re-reading the code.

Find any decision, share it as a link, build on what is already known.

Maps for people, structured context for agents.

For product managers

Follow a feature through the system yourself.

Pick a use case and see every part, data store and host it touches, down to the monthly cost. No code to read, no engineer to wait for.

Hand over a task as a link to its use case and draft: the developer's agent reads the same twin and starts informed.

The task is short because the context is shared.

For business owners

See what AI delivered, and where people decide.

Readiness shows how much of the system is described and settled. The logbook lists the open decisions that still need an engineer.

Compare drafts with their monthly cost side by side, before the money is spent.

Decide on evidence, not on the loudest voice.

Sharing is everything

Sharing is everything.

Software breaks in the gaps between people: an engineer’s lost session, a product manager’s 4,800-word task, an owner’s budget guess, an on-call engineer’s search at 3 a.m.

When every person and every agent reads the same living model, nobody researches the system again, nobody waits for an answer, and nothing is lost when a session ends.

One model. Every reader. Every session.

Direction

Where the twin goes next.

Now: share one picture, read it use case by use case, compare drafts, keep a logbook.

Next: edit on the views and produce Terraform, SQL and prompts. Later: linked to your code, with live load on the map.

Next and later are direction, not yet built.

Get started

Give your team and its agents one picture.

Connect your agent and it starts describing your system.

Self-hosted and open source: your architecture stays on your server. No hosted control plane and no paid edition.

Figures are examples.