Marketing’s AI, engineering’s AI, finance’s AI. None of them know what the others are doing.
GUST-AI is the organisational context graph that connects them. When a budget changes, every dependent decision is re-evaluated. When a policy updates, every governed agent inherits the new rule. When something goes wrong, you can trace exactly what happened, why, and under whose authority.
Teams are building agents in different tools, with different prompts, different data sources, different rules. What starts as innovation becomes an agentic zoo: each agent works on its own, but together they drift, duplicate, contradict, and can’t be audited as a whole.
A scope is a context boundary: a team, a project, a policy domain. Scopes connect to each other with typed relationships (depends-on, influences, subscribes-to, governed-by). The result is a living map of how decisions in one part of your organisation affect every other part.
When context changes in one scope, connected scopes are re-evaluated automatically. You choose the rule per scope: auto-propagate low-risk updates, recommend material ones for human review, block dangerous ones outright. Every step is logged.
Agents accumulate memory as they work: approved decisions, project rules, prior outcomes, handoffs across sessions. What they can see and act on is governed by the scope they operate inside. The agent retains the work it's done. The scope defines what work it's allowed to do. Encapsulation, by design.
Every scope change, every propagation decision, every agent action is logged with who, what, when, why, and under which rule. Built for EU AI Act high-risk system requirements from the start, not bolted on after a procurement review.
Built for the four people who must sign off on enterprise AI.
You cannot put agents into production if you cannot see what they know, what they did, why they acted, or under which rules.
Your teams have invested in LangChain, CrewAI, OpenAI agents. We don't ask you to replace them. We give them a shared context graph, a governance layer, and a memory model they can all bind to.
When marketing changes a campaign, when engineering hits a breakthrough, when compliance updates a policy: every cross-functional decision is re-evaluated, every affected team is told why, every action is logged.
Token costs grow without accountability. AI investments don't map to outcomes. GUST-AI attributes cost by scope, traces decisions to outcomes, and structures context so agents receive only what they need.
Reach out to discuss the right fit for your team and infrastructure.
A chat interface and direct integrations with CRM, HR, marketing, and workflow platforms. Designed for the non-developer interfaces that enterprise coordination requires.
A programmable way to add scopes, change propagation, memory, and audit into existing products and internal systems. The natural choice for platform teams, system integrators, and enterprise engineering.
Run GUST-powered coding agents directly in VS Code for code generation, refactoring, review, documentation, QA, and DevOps tasks. Where the platform first proved out, with scope boundaries and audit trails built in.
GUST-AI is in alpha. The scope engine is running, the graph model is proven, and the architecture is built on the open standards now governing the agentic stack.
GUST-AI is opening access to selected alpha partners. We are looking for teams who want to make agentic AI reliable, governed, and useful in real workflows.
