AI agent governance platform

Approve agents before they act.

REVCLI routes agent work across models, teams, and systems, pauses high-risk steps for named reviewers, and records replay-grade evidence for every run.

Run the governance audit Watch the approval replay

agent run · sales-pipeline · step 3 of 5

approval pending
revcli agent run sales-pipeline
Loading scope: sales-rep · acme-corp
Step 1/5: CRM evidence read done
Step 2/5: Renewal draft prepared done
Step 3/5: Director approval gate waiting
○ Step 4/5: Send approved proposal
○ Step 5/5: Update CRM and evidence packet

Approval required · Step 3 of 5

Acme Corp Q2 Renewal - $84,000

Reviewer: Sales Director Evidence: diff + timestamp

SMB implementation sprint

SMB AI Sprint in 7 days.

Not an AI lecture. A focused sprint to launch one real workflow with your existing tools, team training, and human approval before anything reaches customers or cash.

1 real workflow 7 days Human approval
Take the diagnostic See packages and costs
Revis guiding a small business team through an AI workflow sprint

How it works

Route the run. Gate the risk. Replay the proof.

Every agent run carries owner, scope, approval state, provider route, and replay evidence.

01 - Route

$ revcli run sales-pipeline --gate high-risk
→ role: sales-rep
→ provider: approved-gateway
→ step 3/5: director approval

Operators launch work from the CLI or web console. REVCLI resolves tenant, team, role, model route, and allowed tools before execution.

02 - Approve

Workflow Sales Pipeline
Step Director review
Reviewer Sales Director
Status Pending approval

High-risk actions stop at the configured gate. Reviewers see actor, system, requested action, diff, deadline, and policy reason.

03 - Replay

14:22:01 workflow.started
14:22:04 tool.crm.read
14:22:09 approval.requested
14:26:37 approval.granted · j.torres
14:26:38 tool.email.send

Each run records tool calls, model route, approvals, outputs, and hashes. Owners replay the run without screenshots or guesswork.

Embedded starter

Start the governance audit here

Finish inline or move to the full audit workspace at any time.

Structured 5 steps ~2 min

Why now

Agents are crossing from answers into actions.

Buyers need runtime control points: approvals, provider routing, replay evidence, and policy state across existing systems.

Governance gap Oversight lags usage

Autonomous agent adoption is rising faster than operating controls.

Execution layer Control belongs at runtime

Policy should decide which tools, models, and actions each run can use.

Agent workforce Roles need scope

Every AI worker needs owner, team, permissions, cost, and approval rules.

Buying signal Proof beats pilots

The first workflow must show a gated action, the decision, and a replayable audit trail.

Provider-neutral control plane

Govern any AI, any agent, any model route.

REVCLI sits above the systems of record. It assigns work, scopes tools, routes providers, gates high-risk steps, and records evidence across the run.

Provider-neutral control plane coordinating governed AI team cores
Audit

Map the workflow, systems touched, risk threshold, reviewer, model route, and client-owned usage cost.

Route

Send each run through approved providers and gateways without tying the buyer to one suite.

Authorize

Check tenant, role, team scope, object access, and approval policy before an action executes.

Execute

Let low-risk steps continue. Stop irreversible or external actions at the configured human gate.

Inspect

Capture actor, tool, command, provider, egress, diff, output, approval, and timestamp.

Replay

Reconstruct what triggered the run, what the agent saw, who approved, and what changed.

Team cores

Deploy one governed core before you scale the control plane.

Each core ships one team runtime with scoped tools, approval gates, replay evidence, and rollout support for a measurable workflow.

01

Sales / RevOps Core

Qualify accounts, prepare outreach, update CRM, and hold first-send or discount steps for approval.

02

Customer Success Core

Build renewal briefs, route escalations, prepare QBR packets, and log approved follow-up actions.

03

Finance / Ops Core

Review invoice exceptions, vendor follow-up, spend thresholds, and ledger-ready evidence before posting.

04

Security / Compliance Core

Run policy checks, access reviews, evidence exports, and egress-aware actions with reviewer gates.

05

Engineering / Release Core

Prepare release notes, synthesize tickets, check deployment risk, and gate changes before customer impact.

Packages

Start with one audit. Ship one core. Scale from replay evidence.

The audit selects the first workflow, approval gate, provider route, and rollout scope before a package is proposed.

Start here

AI Agent Governance Audit

Audit-led buying path

Guided diagnostic that identifies the first governed workflow, risk threshold, reviewer path, provider route, and launch plan.

Run the governance audit

First deployment

Governed AI Team Core

One team, one governed runtime

One department gets role-scoped workers, allowed tools, approval rules, audit console, and launch support.

Start with the audit

Multi-team

AI Agent Control Plane

Scale when results are proven

Multi-team SSO/OIDC, provider routing, egress planning, owner visibility, and replay evidence across every core.

Start with the audit

Pricing stays scoped until the audit is complete. We size by workflow risk, team count, deployment posture, support model, and client-owned provider costs. Those costs can include Anthropic API, Bedrock, Vertex, Foundry, LLM gateways, MiniMax, storage, observability, and deployment infrastructure.

Small business buyers can also review the dedicated Claude for Small Business implementation page.

Trust model

Every serious action needs a gate and a replay path.

REVCLI records enough evidence for leadership, ops, security, and the workflow owner to prove what happened after the run.

Revis approval stamp

Provider routing

Human seats are not automation backends.

Licensed humans can use Claude Code in their own attended sessions. Shared or autonomous execution uses Anthropic API, Bedrock, Vertex, Foundry, or an approved LLM gateway.

This gives clients usage tracking, budgets, service credentials, and audit evidence tied to the business workflow.

Owner visibility

Every run captures actor, profile, workflow, command/tool, provider route, approval, egress, output, hash, and replay ID.

Enterprise interface

The web console and CLI are execution surfaces. Personal messaging channels do not trigger governed actions.

Control plane

REVCLI owns catalog, permissions, approvals, policy, and trace correlation. Agents never become the authority.

Egress posture

Production autonomy sends outbound HTTP/HTTPS through CrabTrap or equivalent proxy controls before tools touch external systems.

Category proof

The market is buying agent governance, not agent builders.

REVCLI focuses on runtime control points buyers can test: approvals, provider-neutral routing, replay evidence, and cross-system execution.

Salesforce Agentforce pricing Workday Agent System of Record Microsoft governance and audit UiPath governance foundation Deloitte governance gap McKinsey execution layer Anthropic legal/compliance Claude LLM gateway

Get started

Find the action your agents should not take alone.

The audit maps one workflow, the risk threshold, the reviewer, and the evidence needed before production rollout.

Run the governance audit fernando@waitdead.com

No hidden subscription backend. No system-of-record lock-in. Every high-risk action has approval evidence and replay.