Every action an agent takes is captured as it happens, scored against that agent's own baseline, checked against your rules before it lands, and sealed somewhere an auditor can find it eighteen months later.
Gartner's finding is that enterprises treat agent governance as binary — locked down or fully trusted — and that this is the root cause of failure. Over-restrict a simple agent and you slow delivery and push teams into shadow builds. Under-restrict an autonomous one and you inherit the risk.
Spectre governs by autonomy level. Same trail underneath, different weight of control on top.
Read-only access to sources you name, with output visible only to whoever asked. Summarising a document, retrieving a policy, explaining a block of code.
Produces recommendations, drafts and proposed actions. Still no write access anywhere. The risk moves from data exposure to influence — a confident wrong answer that a tired reviewer waves through.
Writes data, sends communications, changes configuration — but only after explicit approval, every time. Gartner's warning here is approval fatigue: under time pressure, review degrades into clicking yes, and you are left with a false sense of safety over a wider attack surface.
Executes on its own inside defined limits. People review exceptions, audit logs and aggregate outcomes rather than individual decisions — because the agent now acts faster than anyone can watch. Accountability still sits with you.
Autonomy levels after Gartner, "Applying Uniform Governance Across AI Agents Will Lead to Enterprise AI Agent Failure", May 2026. Gartner does not endorse any vendor, product or service described here.
They share one trail, so the team that ships an agent, the team that secures it and the team that has to explain it are reading the same record instead of arguing about three.
Every prompt, tool call, file touched, row read and dollar spent, captured as a structured trace. Scrub back through any run and watch the reasoning arrive in order.
Spectre learns what an agent normally does over its first runs, then scores the distance from it. A new tool, an odd hour, ten times the usual data volume, a retry loop that will not quit.
Rules evaluate before the call leaves the agent, so a blocked action never happens rather than getting cleaned up afterwards. Keep an agent out of a field, cap what it can spend, put a named human on anything above your line.
Every run written to an append-only trail with its approvals attached. Pull an evidence pack for a date, an agent or a single decision, mapped to whichever framework your auditor works from.
Your agents don't change. Spectre wraps the layer where they call tools, which is the one place every action has to pass through regardless of the framework above it.
See what it connects to →Whatever you build with — your own orchestration, a framework, MCP servers, a vendor's agent. Spectre doesn't care which, because it watches the calls, not the code that made them.
Runs in your own cloud account. Every tool call passes through, gets traced and scored, and is checked against your rules before it goes out. Fail open or fail closed — your call.
Databases, warehouses, CRMs, buckets, payment APIs, inboxes. Nothing new to install on any of them, and no endpoint agent on anybody's laptop.
Worth saying plainly, because half the evaluations we lose are ones where the fit was wrong from the start and nobody found out until week four.
Bring an agent you already run. It goes in at Level 1, records everything, blocks nothing — and you decide when it earns the next rung.