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Governance for the Human + AI workforce

Your AI agents are already writing code, closing deals, and touching customer data — almost none of them are governed.

Govern every action your AI agents take.
Block the risky ones. Prove the rest.

Artemy.ai checks every agent action against your policy before it runs, keeps an accountable human on the hook, and records the evidence auditors ask for. It works across your existing tools. Start with Work to assign and coordinate human and AI workers, then add Prism, Guard, and Astra as you grow.

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Atlanta Startup of the Year 2024 (HackerNoon) · SOC 2 in progress
app.artemy.ai — Human + AI Enterprise Control Plane
Dashboard
Confidence Feed
Risk Registry
Intent Graph
AGENT PODS
Operations
Product
Engineering
Management
Policy Engine
Audit Ledger
80/100
Confidence Score
4.2/d
Deploy Freq.
6.1%
Change Fail Rate
47m
MTTR
80
/ 100
Delivery Health
88%
Intent Align.
74%
Dep. Risk
62%
Agent Rel.
95%
🔴
Platform-Core API collision detected
Team Helios · Sprint S-41 · 4h ago
dependency
🔴
Agent privilege escalation — BLOCKED
Coding Agent · Infra write-access · 12m ago
security
🟡
PRD-112 intent drift — 3 stories diverged
Product · Payments Flow · 1d ago
intent drift

AI agents are taking action
across your business. Who's
governing what they do?

Agents now merge code, approve payments, and change customer records, and the old safeguards (human review, separation of duties, a named owner) were built for people. Platform-native controls govern their own platform. Artemy governs across the tools you already run.

🤖
Uncontrolled Agentic Risk
Agents act at machine speed with no identity, no policy, no accountability.
💔
Intent Loss Across Systems
Business intent degrades as it flows from strategy into execution — nothing tracks the drift.
🌍
No Accountable Owner
When an agent acts, the trail often ends at a model version, not a person.
📊
Governance vs Speed False Tradeoff
One control plane removes the tradeoff between moving fast and staying safe.
THE QUESTION EVERY LEADER IS ASKING
"Given everything our agents are doing — how confident are we that we'll deliver what we intended, securely?"
Artemy answers it with a policy check before each action and an evidence trail after it.

One loop for every
autonomous action.

A four-step loop runs on every trigger — a code change, an agent action, a campaign send, a policy violation. Always on, across every domain you connect.

①
Provision · Work
Register human and AI workers, define responsibilities, and assign outcomes. An accountable human is attached to every agent action.
②
Orchestrate · Astra
Break outcomes into subtasks, route them to authorized workers, and recover from failures.
③
Govern · Guard
Evaluate each consequential action before it runs: allow it, require a human override, or block it.
④
Observe · Prism
Attribute activity to identities, evidence human oversight, and report Governance Readiness. Results feed back into Work.

The Artemy Control Plane.

Adopt one product or all four. Work is the front door, and every layer shares the same evidence, identity, and policy model.

Artemy Astra
Execute · Orchestrate · Deliver
Governed AI Workers & autonomous execution.
BUILT FOR CEO · CTO · CAIO
Artemy Guard
Govern · Secure · Control
Runtime enforcement, policy & agent identity.
BUILT FOR CTO · CIO · CAIO
Artemy Prism
Observe · Analyze · Predict
Attribution, oversight evidence, and Governance Readiness across every tool.
BUILT FOR CTO · CIO
Artemy Work
Operate · Coordinate · Assign
The front door. Assign outcomes to human and AI workers, hand off in Slack, and keep an accountable human on every agent action.
BUILT FOR CEO · CTO · CIO
🔎 Attribution 🧭 Workforce Ops 🛡️ Policy Engine ⚙️ AI Worker Pods
Organizations start with Work, add visibility, establish governed boundaries, and finally unlock safe autonomy — one platform, four products.
One model. Every domain.
⚙️ Engineering 📣 Sales & GTM 💳 Finance 🎧 Customer Support 📦 Procurement + Any domain you add next
Every layer, enterprise-ready from day one:
SSO / SAML / RBAC SOC2 (in progress) SaaS · Private Cloud · On-Prem PII Redaction

One platform.
Every leader gets
what they need from it.

Most teams start with the CTO or CIO. Work, Prism, Guard, and Astra answer different questions for different seats at the table, and you can buy one or all four.

🧑‍💻
For the CTO
Ship fast without losing control
Know what agents are doing to your codebase and infra — and stop the risky ones before they merge.
  • One confidence score across human + AI delivery
  • Runtime policy gates on every agent action
  • Immutable audit trail for every decision
🗂️
For the CIO
One governed platform, not a dozen tools
Bring every AI initiative under one auditable system of record and one identity model.
  • Single system of record for human + AI work
  • Consistent identity, access & policy for every agent
  • SSO/SAML, RBAC, audit-ready architecture
📈
For the CEO
Proof, not promises, on AI ROI
Turn AI adoption into predictable delivery and margin, with evidence the board can trust.
  • Board-ready evidence of throughput & quality gains
  • Autonomy earned through observed behavior, not assumed
  • Pilot to live guardrails in as little as six weeks
🤖
For the CAIO
Scale AI workers responsibly
Govern every agent and AI worker you deploy under one framework, across every domain you add next.
  • One governance core across coding, GTM & beyond
  • Behavioral risk profiles that travel with each agent
  • Infrastructure to scale from pilot to AI workforce

Know where your AI creates risk
before it becomes a problem.

Artemy AUDIT helps organizations discover their AI landscape, assess governance and risk gaps, and build a practical roadmap for governing AI systems, agents and AI workers.

  1. 1Discover your AI reality.
  2. 2Assess the risks.
  3. 3Build the roadmap.

Artemy AUDIT provides your AI Governance Blueprint

Every Artemy AUDIT engagement produces a practical set of deliverables:

Discover

AI Inventory

What AI exists across the organization.

Assess

AI Risk & Governance Assessment

Where governance capabilities and controls are missing or immature.

Assess

AI Risk Register

The material risks associated with identified AI systems and use cases.

Assess

Governance Gap Analysis

Current state versus defined governance requirements.

Build

AI Governance Operating Model

Roles, responsibilities, decision rights and accountability.

Build

Policy & Control Recommendations

The policies and controls needed to govern AI effectively.

Build

Prioritized Roadmap

What to address now, next and later.

Report

Executive Governance Report

A concise view for CIO, CTO, CISO, Legal, Risk and Compliance leadership.

Agents are governed actors,
not trusted tools.

Every agent operates under explicit identity, least-privilege scope, and continuous behavioral monitoring — coding, sales, finance, support. Autonomy is earned, not granted by default.

Every
consequential agent action
checked against policy before it runs
1
accountable human
attached to every agent action
Any
tool or vendor
governed under one identity, evidence, and policy model
☠️
Prompt Injection & Hallucination
A bad input or model error pushes an agent to leak data or make an unauthorized change.
Guard validates every output against policy before it executes.
🔓
Privilege Escalation
An over-permissioned agent — in code, CRM, or finance — touches something it shouldn't.
Least-privilege scoping blocks unauthorized access before it happens.
👻
Shadow Changes & Drift
Agents make undocumented changes that bypass review and compliance gates.
Every agent-driven change is traceable, attributable, and logged.
⚡
Cascading Failures
Unbounded automation triggers blast-radius failures before a human can step in.
Blast-radius limits auto-escalate high-risk actions to a human.
📋
Compliance & Audit Gaps
Agent actions leave no trail in existing tools — a problem in every regulated function.
An append-only ledger auto-generates audit evidence to support SOC2/SOX reviews.
🕳️
Supply Chain Exposure
Agents pull in new dependencies or vendors without vetting, quietly widening risk.
Dependency risk is a scored dimension — not a blind spot.

Three modes.
One enforcement layer.

The Policy Engine doesn't wait for incidents — it evaluates every human and agent action before it executes. Organizations progress through enforcement modes as their governance maturity grows. In every mode, each action gets one decision: allow, require override, or block.

Advisory
Surfaces risks and policy violations
Recommendations only. No blocking. All decisions remain with humans. Ideal for establishing a baseline understanding of agentic risk exposure.
Approval
Routes high-risk actions to defined approvers
Human sign-off required before high-risk agent actions proceed. Scope, blast radius, and confidence thresholds determine what escalates.
Blocking
Autonomously blocks unsafe or non-compliant actions
Real-time enforcement. Unsafe agent actions never execute. Every block is logged with full attribution to the Security Evidence Ledger.
🔒 Security Evidence Ledger — Live Feed
12:04
Coding Agent attempted write access to infra/prod-config.tf — outside scope boundary
BLOCKED
12:01
Deploy Agent — staging deployment · confidence 91 · blast radius LOW · policy compliant
APPROVED
11:58
QA Agent created 14 test cases · linked to PRD-117 spec · intent alignment verified
LOGGED
11:47
Coding Agent — 3rd-party dependency lodash@4.17.11 — known CVE detected, escalated
ESCALATED
11:39
Integration Agent synced 47 Jira events · 0 policy violations · full attribution stamped
LOGGED
Immutable. Append-only. The Security Ledger enables full system replay, forensic root-cause investigation, and audit-ready evidence to support SOC2/SOX/ISO 27001 reviews.
⚔️
Artemy cannot be acquired as a feature. It must be a new layer.
Existing platforms lack cross-system authority, unified data models, and runtime enforcement. Security and governance require authority across systems, not within them — which is exactly what Prism, Guard, and Astra provide together.

Autonomy is earned.
Not assumed.

Autonomy unlocks only when confidence and security controls support it. Agents progress through governance-gated levels — in any domain.

Level 1 — Observability
01
Read-Only Signals
Agents collect signals. Humans review everything. Zero write access.
Risk detection · Signal ingestion · Trend analysis
Level 2 — Intelligence
02
Detect & Recommend
Agents surface risks and recommendations. Humans keep every decision.
Anomaly detection · Drift alerts · Policy advisory
Level 3 — Prediction
03
Forecast Risk
Agents forecast outcomes and exposure. No autonomous action yet.
Sprint simulation · Blast radius estimates · Risk forecasting
Level 4 — Governed Autonomy
04
Act Under Policy
Agents act within strict confidence and risk thresholds. High-risk actions still escalate.
Auto-remediation · Gated deployments · Policy-bounded actions
Autonomy level adjusts continuously — based on observed behavior, policy compliance, and risk.
0
Ungoverned agent actions
Every action identity-attributed & policy-evaluated
↓30%
Coordination overhead
Measured in pilot customers
100%
Agent action auditability
Immutable Security Evidence Ledger
90d
Pilot to production
Read-only start, no workflow changes

What a 6-week pilot delivers

Read-only visibility in week one. Live guardrails by week six. Measurable at every stage.

Week 1–2 · Visibility
"One version of delivery reality — not five PowerPoints from five managers."
✓ Confidence Score live, day 1
✓ Top 5 risks surfaced with evidence
🔒 Every agent action mapped
Week 3–4 · Prediction
"We stopped reacting and started preventing. Planning stopped being a guess."
✓ Over-commitments caught early
✓ Cross-team blockers visible in advance
🔒 First ledger entries, full attribution
Week 5–6 · Control
"The confidence score is in every executive meeting now."
✓ Executive ROI report, full attribution
🔒 Policy engine live — high-risk actions escalate
🔒 Audit-ready evidence package generated
75%+
of surfaced risks validated as real by your own managers
100%
of agent actions attributable & forensically replayable
4+
days per week leaders rely on the Astra Brief
6wk
from first signal to live guardrails

Start with visibility.
Scale with confidence.

Every plan begins read-only. Guard is billed at $1 per enforced action on top of the plan, and every tier shares the same identity, evidence, and policy model.

Monthly
Annual Save 20%
Starter
🛡️
Starter
For pre-seed teams putting their first agents under policy.
Starts at
$9.99
per month · 1 pod · up to 5 workers
  • ✓Guard: Intent Check
  • ✓Connects to GitHub, Jira, Slack, Claude Code, Codex, Cursor, AWS
Start Pilot
Pro
🔎
Pro
For Seed stage teams executing Agentic workflows.
Starts at
$99
per month · 1 pod · up to 10 workers
  • ✓Work: outcomes, workforce registry, handoffs
  • ✓Guard: policy engine (allow, require override, block)
  • ✓Prism: lite attribution and evidence reports
  • ✓Connects to GitHub, Jira, Slack, Claude Code, Codex, Cursor, AWS
  • ✓Astra: Basic AI Worker orchestration + optional Basic AI Worker add-on
+ $1 per enforced Guard action, billed on top of the plan.
Start Pilot
Enterprise
🛡️
Enterprise
For enterprise software and IT teams that need runtime enforcement and audit exports.
$9,999
per month · 50 pods · 500 workers
  • ✓Everything in Growth
  • ✓Guard Premium: runtime interception at the action boundary
  • ✓Third-party and vendor agent governance
  • ✓Prism: NIST, SOC 2, and ISO compliance exports
  • ✓Astra: Premium AI Worker orchestration + optional Premium AI Worker add-on
  • ✓SSO/SAML, custom domain adapters, dedicated CSM
+ $1 per enforced Guard action, billed on top of the plan.
Contact Sales

Connect in 48 hours.
See agent risk in week one.
Enforce policy by week six.

A 6-week read-only pilot with no workflow changes. Connect your tools in under 48 hours, see agent risk in week one, and turn on full policy enforcement by week six. Or start a free 7-day Starter trial.

No credit card required · SOC2 compliance underway · Agent identity & access control from day one · Connect in < 48 hours · Free 7-day Starter trial