Every developer's AI works alone. They lose context and break each other's code. Ours share one memory, and test what they build.
Your agents share one memory. Everything gets cheaper and sharper.
Across teams, machines and sessions. No duplicated work, no collisions.
Sharp context beats big context. Smaller models, same answers.
Agents drive your product and prove the result. Your team stops re-testing.
Code, docs, runs and agent history. One place. Everything reads it.
Use one and it works. Use two and both get better.
Coding agents that don’t work alone. They see what your teammates’ agents are doing, learn from what broke in testing, and run on cheaper models because the context is sharp.
QA that reads your code, drives your product, and proves what broke, with the request and the screenshot attached. Plus docs and projects that stay true to the code.
One data layer your whole organisation and its agents can read. Ships with Flow Console and Artel, nothing extra to buy, nothing to configure.
Turn the systems your team already runs into governed tools your AI agents can use. ERP, CRM, helpdesk, that homegrown admin panel. Described in plain English, secured by your own application, kept healthy for you.
Smaller products in the ecosystem. Same account, same data layer.
Spectre is Metantel's advanced-projects division. Long-horizon programs in physical AI, autonomy, and simulation. Its work reaches the public first as capability in our products: the engine at the core of Flow Console started as a Spectre program.
Simulation, Collapsed to an Intent
PROGRAM OVERVIEW →Physical AI, at the Edge
PROGRAM OVERVIEW →Many Assets. One Picture.
PROGRAM OVERVIEW →NOTE Program pages reflect publicly releasable information. Specifications and milestones are disclosed as programs mature.
Every developer has an AI assistant now. Each one sees only its own window, so they duplicate work, contradict each other, and quietly break code another engineer's agent depends on. Adding more assistants makes it worse.
We gave them one shared memory. Your team's agents see each other's work as it happens, and a QA agent tests what they ship and proves what broke. You get output you can actually trust.