Agents are changing work.
Control should keep up.
We’re building the control plane for the agentic enterprise: a shared way to govern what agents use, what they do and how they improve.
Agentic work crossed from answering questions into using tools, accounts and business systems. DriftGate exists to make that work accountable without forcing every team into one model or runtime.
Intelligence can be flexible.
Authority should be explicit.
As agents move beyond generating answers, they begin touching the systems that businesses depend on. Each new client, tool and workload can introduce another set of permissions, configurations and logs.
DriftGate brings those responsibilities into a connected model. Approved environments. Current authority. Bounded effects. Evidence that survives uncertainty. Improvements that are tested and reviewed before they spread.
The starting point can be one developer’s fragmented AI setup. The same model can extend to shared team infrastructure and organization-wide agent operations.
Gate the action.
Understand the drift.
Keep the lesson.
Work became agentic. Control stayed fragmented.
A useful agent may move among a coding client, a hosted workflow, a knowledge source and an external system. Each surface can carry its own tools, instructions, permissions and records. When a task fails or changes, the operator has to reconstruct which setup was active, whose authority applied and whether an outside effect happened.
That problem can begin with one person working across devices and projects. It becomes a company problem when teams share agent infrastructure, delegate consequential actions and need to explain an outcome later. DriftGate's purpose is to connect environment, authority, action, evidence and improvement in one operating model.
Flexible intelligence needs explicit authority.
Models and runtimes can vary. The source of authority for a customer refund, production change or private data read cannot be inferred from a prompt alone. The governed request needs an actor, resource, operation, current scope and a decision at a boundary capable of affecting that operation.
Evidence then has to distinguish the decision from the effect. An approval can expire or be revoked; an allowed request can time out after the provider acts; a trace can describe behavior without being able to stop it. Those differences shape the platform.
The work connects through a loop.
The loop serves a personal project, a shared team baseline and an organization-wide standard without converting a private lesson into shared authority by accident.
Gate the action
Check current identity, policy and approval before a consequential effect at a qualified boundary.
Understand the drift
Compare intended configuration and behavior with what is actually observed; investigate the divergence.
Keep the lesson
Test a candidate change independently, review it, release to a defined audience and retain rollback.
A control plane around the work you already run.
DriftGate is designed to sit around existing coding harnesses and standalone agentic products, including voice, support, sales, finance and custom workflows. The planner, model and runtime can remain external. API and SDK paths express governed intent at the consequential operation; MCP and qualified ACP integrations are entry points, not automatic enforcement boundaries.
The platform direction spans six control domains and reviewed learning. Each integration still needs its own authority, effect boundary and release qualification. A visible connection or website description alone does not establish that a control is running.
Read the evidence for what it is.
The 24 workflows on this site use example data to explain control design. Two incident analyses discuss attributed public research and the control lessons it suggests. Neither is a DriftGate customer deployment or proof that DriftGate prevented the reported event.
Release and integration behavior need qualification in the target environment; the availability page explains how to read platform scope and control modes.