CONTINUOUS AI GOVERNANCE THAT UNDERSTANDS YOUR AGENTIC WORKFLOWS: AGENTS, PROCESSES, TASKS, EVIDENCE

Recorded.
Governed.
Provable.

The governance layer between your AI agents and your regulators. Every workflow understood, every setup checked, every run governed. Prove compliance at every inference, not every quarter.

Built with the support ofMicrosoft for StartupsGoogle for Startups Cloud Program

Where governance starts

You can't govern what you don't understand.

EvidentAI understands your agentic workflows first: the agents, the processes and tasks each one runs, what every decision saw. Governance binds to that understanding, at setup, at every run, and when the examiner asks why the AI said what it said.

The Problem

AI is being wired into decision workflows that carry regulatory weight.

The governance stack was built for a world before AI inference. Policies exist on paper. Evidence is pulled after the fact. No one can reconstruct what the AI actually saw.

Fragmented visibility

AI usage is scattered across teams, models, and vendors. No single view of what agents exist or what they do. Shadow AI is a known problem with no known solution.

Policies without teeth

AI policies exist on paper but are never evaluated at runtime. Controls fire before or after execution, never during. Your policy framework has no connection to your AI behavior.

Unreconstructable decisions

When the examiner asks why the AI said what it said, you cannot reconstruct the inputs, policy context, or retrieval state. Audit response takes weeks, not hours.

What we do

The governance layer your AI decisions need.

EvidentAI understands your workflows, then sits between your AI agents and your regulators: checking setup, evaluating policy, recording decisions, and producing audit-grade evidence continuously.

Verify the setup

Configuration checked in the context of the workflow the agent serves. The workflow's policy decides which tools an agent may hold and which models it may call, before the first run.

Evaluate & enforce

Your AI policies are evaluated at every inference, not every quarter. Risky actions are blocked, routed, or held for human sign-off before they complete.

Record & reconstruct

Full decision context captured at runtime, reconstructable on demand with regulator-grade integrity. Answers in minutes, not weeks.

Govern the workflow

Credit decisioning, claims processing, care navigation: governed end to end, with every agent, tool call, and human checkpoint visible as a step.

Secure the surface

A continuously updated AI vulnerability catalog, mapped to , shows where your agents are exposed and which defenses cover them.

Inside the platform

Agent inventory

Every agent, model, and tool in the estate, discovered and assigned an owner.

Configuration checks

Agent setup evaluated against the policy of the workflow it serves. The failing setting is named, and so is the task that makes it wrong.

Build gate

A workflow whose configuration violates its own policy is blocked in CI before it deploys.

Drift detection

Approved configuration compared with what is running. Divergence raises a finding.

Workflow governance

Register a decision workflow once. Every run is tracked end to end, with evidence.

Human sign-off queue

Risky actions wait for a named reviewer before they complete.

AI vulnerability catalog

Known AI weaknesses matched to your agents, ranked by severity.

MITRE ATLAS matrix

AI threats mapped in the industry-standard threat language.

Evidence packages

Findings, runs, and sign-offs compiled for examiner review.

Policy explorer

Your policies and controls, bound to the AI systems they govern.

NIST AI RMF mapping

Controls mapped to the NIST AI Risk Management Framework.

Bias cohort monitoring

Outcomes compared across customer groups to surface unfair patterns.

PII shield

Personal data detected and redacted before it leaves the system.

DSAR workflow

Privacy requests tracked, fulfilled, and evidenced.

Token budgets

AI spend metered per workflow, with limits that enforce themselves.

Workflows & agents

Agents are governed in the context of the workflow they act in.

Every agent, tool call, and human checkpoint is visible as a step. Every run produces evidence. One policy governs the whole path.

Setup

Registered & checked

The workflow and its agents are declared, and their configuration passes policy before anything runs.

Agent

Intake & draft

The agent acts inside the workflow: credit decisioning, claims triage, care navigation.

Tool call

Retrieval & state

Inputs, retrieval state, and context captured at the moment of inference.

Policy gate

Checked against policy

Decided in the request path: allow · route · block · sign-off.

Human checkpoint

Sign-off queue

Risky actions held for human review before they complete. Human review is a step, not an afterthought.

Evidence

Record sealed

The run produces an audit-grade record, reconstructable on demand.

OCC · FDIC · SEC · FINRA · EU AI Act: examination priority

How we're different

Not monitoring. Not model-level. Not another GRC.

Examiners ask two things: show the decision, and show the control that governed it. Answering both takes a system that understands the workflow and sits in its inference path.

PATH

Enforcement, not observation

Observability tools tell you what happened after the fact. EvidentAI decides in the request path: allow, route, block, or hold for human sign-off before the action completes.

UNIT

The workflow is the unit

Model-level controls miss the decision, and per-agent posture checks miss the context. EvidentAI governs the workflow end to end, so every agent, tool call, and human checkpoint answers to the same policy, at setup and at every run.

FEED

We feed your GRC, not replace it

Your control library lives in OneTrust, Archer, or ServiceNow. EvidentAI maps it once and streams continuous AI evidence into the systems your assessors already trust.

Who it's for

Built for regulated enterprises deploying AI.

Where AI decisions carry regulatory weight and audit exposure, and where "we have an AI policy" is no longer a sufficient answer.

FS · HC

Financial services & healthcare

Banks, insurers, asset managers, and health systems deploying LLM-powered applications into decision workflows: credit decisioning, underwriting, claims processing.

GRC · RISK · CTO

GRC, risk & technology leaders

GRC leaders, risk officers, and CTOs who need to prove to examiners that every AI-assisted decision was governed by policy, not just monitored after the fact.

EXAM

Exam-driven urgency

OCC, FDIC, SEC, and FINRA have made AI governance an examination priority. EU AI Act high-risk obligations are approaching. The window to get governance right is closing.

Product preview

Governance, from setup checks to enforcement in the request path.

app.evidentai · /overview

Overview dashboard: compliance score, policies, controls, agents, alerts.

OverviewCompliance score, fleet risk, and the action queue at a glance.

app.evidentai · /connections

Connections: native control-plane connectors that feed AI Posture.

EnvironmentLive posture across every AI connector and control plane.

Get in touch

See EvidentAI
in action.

We're selecting a small number of founding design partners to shape the platform against real governance requirements. Founding partners get direct access to the team, influence over the roadmap, and preferred terms. Prefer to talk first? Book a live demonstration, remote or in person.

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Controls in an AI context