The First Real-Time Control Layer For Teams Using Coding Agents

When two galaxies merge, almost none of their stars collide.

the problem

What we solve

01

drift

Each agent decision moves a little further from what you meant. The longer the task, and the more micro-decisions depend on each other, the faster it gets worse.

02

conflict

AI code ships faster than a team can agree on every detail. The direction is aligned, but the small decisions may not be. Each dev’s coding agent carries the conflict forward, and it compounds.

03

no trace

There is no auditable record of what agents and humans decided, or why. Debugging is slow. The code is hard to understand. No human can detect drift and resolve conflicts in real time.

We coordinate your agents in real time.

  • glad.graph
    G

    Graph

  • glad.lineage
    L

    Lineage

  • glad.agent
    A

    Agent

  • glad.decisions
    D

    Decisions

Every single micro-decision a developer's agent makes is recorded with full past and present relational context and evaluated against all other agent decisions happening in the team, in real time.

We catch when decisions made by agents and/or humans conflict with each other and GLAD allows your agent to trace back its decisions and self-correct based on human intention and past decisions. All decisions made in a project are auditable both as they're being made, and later on.

Transform the way you code

A classifier‑native multiplayer IDE.

Coming soon

First of its kind

222–255ms

median per check, on real recorded calls: the fastest checks of any control layer for coding agents

Architecture
Built natively around a classifier model, so every decision your agents make is checked against the whole team's as it happens, fast enough to sit inside every turn.
Input
Only the excerpt a check needs: one change and the few decisions it could touch
Cost
The cheapest to run: the infrastructure keeps every check small, so checking every turn of every agent costs little
Accuracy
Finds 93–94% of the relevant context for every agent request.
Runs
At every prompt, every time an agent stops, and every few minutes through long work
Method
Every question measured on labelled real work; its wording fixed until remeasured

Security

Private cloud

On your own AWS account.

On premise

On your own servers.

Local first

On your own laptop.

talk to the founders

Supercharge your team.

Contact