ModelCop
Pre-launch · May 2026

Govern the AI. Prove it.

The runtime control plane for AI governance and non-human identity security.

Get in touch → Read the brief
100:1
Non-human identities now outnumber humans in cloud-native orgs.
Palo Alto Networks, 2026
70%
Of identity incidents in 2025 originated from AI-related activity.
Microsoft Secure Access Report, 2026
68%
Of organizations cannot distinguish AI agent activity from human.
CSA + Aembit Study, 2026
01 · The Problem

Every enterprise has lost track of who is acting on their behalf.

Non-human identities — service accounts, API keys, agentic workloads — now drive the majority of cloud-native activity. AI agents make decisions, call tools, and move data with no governance layer between them and the systems they touch.

100:1
Non-human identities now outnumber humans in cloud-native orgs.
Palo Alto Networks, 2026
70%
Of identity incidents in 2025 originated from AI-related activity.
Microsoft Secure Access Report, 2026
68%
Of organizations cannot distinguish AI agent activity from human.
CSA + Aembit Study, 2026

Existing identity tools were built for people. Existing AI guards were built for models. Nobody owns the intersection.

02 · The Platform

One platform. Two capabilities. Six agents.

ModelCop is the integration. Built on the principle that every prompt has an identity, and every identity has a chain of accountability — from request to model to data to the human who owns it.

01 · Runtime AI Governance

Every prompt, governed at the wire.

Drop-in via base-URL configuration. Hard enforcement at the wire, not advisory — every decision logged.

  • 11 LLM providers governed inline — Anthropic, OpenAI, Bedrock, Azure, Vertex, Mistral, Cohere, and more
  • 8-class data classifier: PII, PHI, PCI, ITAR, CUI, secret, internal, public
  • Hard block, redact, warn, or log — with an HTTP error and a forensic record on every decision
  • Policy engine surfaces explainable decisions to investigators, auditors, and the LLM caller itself
02 · NHI Identity Security

Every identity, with a chain of accountability.

Every prompt grounded in the identity that requested it. Every identity grounded in a human owner. End-to-end forensic trail.

  • 30+ connectors correlate and identify NHIs across Okta, Entra, GitHub, Vault, AWS, GCP, Azure, and more
  • Source-system enforcement (enterprise): rotate, disable, or revoke against the source — not just alert
  • Behavioral baselines, just-in-time access, ephemeral broker tokens for AI agents
  • Single-query forensic chain: prompt → NHI → human owner, in three clicks
Powered by six capability agents: Cadence · Tether · Compass · Sentry · Forge · ModelCop
03 · Capabilities

From correlated signal to enforced action — and the evidence in between.

Five capabilities that turn the identity graph into something a CISO can act on, a CFO can price, and an auditor can read. Each grounded in live data, not slideware.

001 · INLINE ENFORCEMENT

Block the prompt before it reaches the model.

Point an agent's provider base URL at ModelCop. Every request is classified and checked against your policy before it's forwarded — a policy-violating prompt is blocked, the agent receives a native API error, and a forensic record is written. OpenAI- and Anthropic-compatible today.

Governs traffic routed through ModelCop · transparent network enforcement available per environment

002 · ATTACK PATH & BLAST RADIUS

Trace an event to the identity — and the human who owns it.

Every AI security event traces back to the non-human identity that executed it and the accountable human chain behind it: owner → manager → department. Kill-chain, force-graph, and blast-radius views make the attribution legible in seconds.

Event → NHI → human owner · forensic detail on every node

003 · CROWN JEWELS

Identify the assets that actually matter — for your team to confirm.

ModelCop flags likely-critical assets from the sensitive data interacting with them, then traces which non-human identities can reach each one. A preliminary identification for your SMEs to validate — not an autonomous determination — so the human judgment stays where it belongs.

Correlation-driven · SME-validated · priced against the value you set

004 · RISK IN DOLLARS

Rank exposure by what it would cost — not by a severity label.

Every NHI and data class is priced to a dollar-denominated risk figure. Instead of a wall of "high / medium / low," your board sees exposure ranked by what a breach of each identity would actually cost — the language risk committees and CFOs already speak.

Per-identity · per-data-class · board-ready

005 · ATTESTATION CENTER

Every control assertion, backed by live evidence you can show.

Attestation status across your controls, each row linked to the source data that proves it — not a spreadsheet someone updated last quarter. Walk an auditor through exactly how a control is satisfied, where the gaps still are, and export the whole thing as audit-grade evidence packs mapped to the frameworks that matter.

Live evidence · control-to-source linkage · regulator-mapped export

006 · PAYS FOR ITSELF

Priced in the same dollars as its own invoice.

ModelCop reclaims 38–62% of over-provisioned access in the first 90 days — real licenses and standing privilege handed back — and prices the exposure it removes in dollars. Set both against the per-NHI price on this page and the platform funds itself: the access it recovers and the risk it retires are measured in the same currency as its cost.

Reclaimed scope + retired exposure − platform cost · the math is yours to run

Correlate the signal. Enforce the policy. Prove every decision — and pay for the platform with what it recovers.

03.5 · How You Connect

Four ways to integrate. One enforcement gate. Zero code required for the first.

Most AI governance tools require you to rebuild your stack around them. ModelCop meets you where your agents already run — a base-URL swap is enough to put every prompt behind a hard enforcement gate. More control is available as you need it.

METHOD 01 · ENFORCEMENT PROXY INLINE

Drop-in base URL. Zero code change.

Redirect your existing OpenAI or Anthropic SDK to ModelCop's proxy endpoint. Every prompt is classified and gated before it reaches the provider. A blocked call returns a native API error — your agent code doesn't change.

OPENAI_BASE_URL=https://console.modelcop.ai/proxy/openai/v1 ANTHROPIC_BASE_URL=https://console.modelcop.ai/proxy/anthropic
INLINE ENFORCEMENT
Block before provider is reached
DATA-CLASS GATE
PHI / PCI / ITAR / CUI blocked per policy
CODE CHANGE
None — one environment variable
LIMITATION
Only governs traffic routed through the proxy — pair with egress control to catch shadow calls
METHOD 02 · NATIVE API INLINE

Call ModelCop directly. Swap providers without touching app code.

Apps call /api/llm/complete with ModelCop's schema. ModelCop selects the tenant's active backend provider and forwards — meaning you can move from OpenAI to Bedrock to Azure OpenAI by changing one setting in the console, not by redeploying your agents.

INLINE ENFORCEMENT
Full gate — same as proxy method
PROVIDER PORTABILITY
Swap providers without app redeploy
CODE CHANGE
Requires adopting ModelCop's request schema
LIMITATION
Response is ModelCop's normalized format — not raw OpenAI/Anthropic wire; SDK parsers need adaptation
METHOD 03 · LLM CONNECTOR INLINE

ModelCop holds your provider keys. Your agents never see them.

Save provider credentials in ModelCop once. ModelCop brokers every outbound call — your agents carry ModelCop tokens, not provider API keys. Rotate, revoke, or switch providers from the console. Governance policy is applied automatically the moment a connector is configured.

CREDENTIAL BROKERING
App never holds provider key
POLICY ON BY DEFAULT
Governance row created at connector setup — status: pending until admin sanctions
KEY ROTATION
Console-only — no agent redeploy
LIMITATION
Requires method 01 or 02 for enforcement — the connector is the credential store, not an enforcement surface on its own
METHOD 04 · PASSIVE MONITORING OBSERVE

Log shipping and SOC integration. No traffic redirection required.

Ship provider logs, SIEM events, or webhook payloads into ModelCop for historical analysis, anomaly detection, shadow AI discovery, and compliance evidence generation. No inline gate — but full forensic capability: denial forensics, counterfactual replay, prompt lineage, and fleet incident tracking all operate on ingested data.

INLINE ENFORCEMENT
None — violations detected after the call
DEPLOYMENT CHANGE
None — log shipping only
FORENSICS & EVIDENCE
Full — lineage, replay, anomaly, compliance
LIMITATION
Cannot block, redact, or cap spend in real time — best paired with method 01 or 02 for enforcement coverage

Enforcement is on by default. Every connector configured is a governance policy created — status: pending until you sanction it. No traffic reaches a provider without a policy decision on record.

04 · Why Now

Two markets collided in 2025–26 — and the incumbents got bought.

The window for an integrated AI governance + NHI platform is open for roughly twelve months before a non-acquired vendor builds the bridge. Mid-market and enterprise buyers want a focused vendor, not a Cisco / Palo Alto / Check Point bundled feature.

Q3 2024
EU AI Act passes. The NHI category emerges from secrets management.
Sept 2025
Check Point acquires Lakera. Best-in-class AI runtime guard becomes a bundled feature.
March 2026
Cisco announces $400M acquisition of Astrix. The NHI category leader absorbed.
March 2026
Oasis Security raises $120M Series B for agentic access management. Category validation.
Today
Both capabilities are now compliance surface for NIST AI RMF, EU AI Act, NYDFS 500, DORA, HIPAA, and CMMC.

The next platform is the integration. We've spent twelve months building it.

05 · Pricing

Per-NHI subscription. Four tiers. 20% under median market.

Transparent pricing because we believe in it. Annual contracts. Volume discounts at scale. All tiers include the full platform — runtime governance, evidence layer, and the six capability agents.

Team
≤500 NHIs
$4.00
per NHI / month
Annual Floor
$36K
Business
500–5K NHIs
$3.40
per NHI / month
Annual Floor
$96K
Enterprise
5K+ NHIs
$2.70
per NHI / month
Annual Floor
$324K
Sovereign
Federal / IL5
Custom
GovCloud + CMMC L3
Annual Floor
$750K+
Standard procurement terms: annual contracts · net-30 payment · multi-year discounts · standard MSA available on request
Savings Calculator

Run the math yourself.

Every number below is editable and every assumption is shown. We don't hide a multiplier — we give you the inputs and the formula, and let the arithmetic make the case.

50%
Assumptions (editable)
75%
30%
—
net annual benefit
Access reclaimed hard $ — recovered licenses & standing access —
Exposure reduced risk reduction, not cash —
ModelCop cost — —
Illustrative estimate based on the inputs above. Hard $ reflects recoverable access cost; exposure reduction is avoided-loss, not cash savings. ModelCop cost uses published per-NHI list pricing. Your actuals depend on your environment — we'll model them with you in a working session.
06 · Trust

Built on Trust by Design.

Two kinds of trust matter here: trust in the platform's safeguards, and trust in the founder's record. We are explicit about both.

✓
Texas LLC, formed and active
May 2026
✓
USPTO Trademark filed
Serial 99841440
→
SOC 2 Type II — In progress
Target Q4 2026
→
ISO 42001 controls implemented
In observation
✓
Compliance frameworks mapped
23 frameworks
✓
Identity connector kinds
30+ connectors
David Stanton, Founder & CEO of ModelCop
David Stanton
Founder & CEO

Built by a CISO for CISOs. ModelCop was built in response to the question David's clients kept asking through 25+ years of consulting: "Are there any proven AI security and governance solutions for non-human identities?"

  • 25+ years in technology, compliance, and cybersecurity professional services
  • 9+ years in interim and CISO leadership across regulated industries
  • Big 4 / top consulting: PwC · Accenture · Protiviti
  • Direct relationships with Fortune 1000 CISOs across banking, healthcare, manufacturing, and defense
07 · Get in touch

Tell us what you're trying to govern.

We take a small number of partners each quarter. Reach out and we'll set up a 45-minute call to walk you through the platform and understand your environment.

Partner intro
Book a 45-minute call
Walk through the platform & your environment
Schedule a demo
Book a 45-minute walkthrough
Live demo on Microsoft Teams · NDA available on request

For investor inquiries: David is currently raising a pre-seed round. Mention investor interest in your subject line and we'll respond with the executive summary, deck, and round terms. → dstanton@modelcop.ai

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