The governance gap in enterprise AI agents
Enterprise compliance frameworks (SOC 2, ISO 27001, NIST AI RMF, EU AI Act) increasingly require organizations to document how autonomous AI systems behave. Current observability tools answer "what did the agent do" — they rarely show when execution structure stops converting cleanly into progress.
The CAUM receipt answers a narrower question: what structural evidence appeared in the run, and what hash commitments make that evidence reviewable later.
This distinction matters for audit, legal, and governance teams. A CAUM receipt is evidence for structural review, not a semantic correctness certificate.
Enterprise use cases
Legal & Compliance Agents
Law firms running autonomous due diligence, contract review, or compliance agents need per-session audit artifacts. CAUM receipts provide structural evidence without reading client matter content.
Financial Services
Banks and trading firms deploying autonomous coding agents face OCC, FRB, and SEC scrutiny of AI systems. CAUM's observation receipts can support model risk review without claiming semantic correctness.
Healthcare & Life Sciences
HIPAA-covered entities using AI agents for clinical documentation, coding, or research need behavioral audit trails. CAUM reads zero semantic content — compliant with zero-trust data access policies.
Enterprise DevOps
Engineering orgs running 10K+ agent sessions/day can expose measurable compute cost to loops and stagnation. CAUM quantifies structural exposure per session and enables real-time review before sessions reach CRITICAL tier.
The structural receipt
Each monitored session can produce a JSON receipt with structural health tier, loop/cycle evidence, cost/token counters when provided, and hash-chain metadata for later review.
"session_id": "sess_a7f3c2e1d4b9",
"model": "gpt-4o",
"framework": "openhands",
"uds": 0.847, // health score 0–1
"tier": "T2", // T1=OK T2=MONITOR T3=WARNING T4=PRE-CRITICAL T5=CRITICAL
"regime_dist": {
"EXPLORER": 0.71,
"GRIND": 0.19,
"STAGNATION": 0.07,
"LOOP": 0.03
},
"structural_exposure_pct": 3.8,
"steps": 47,
"resolved": true,
"timestamp": "2026-03-24T18:42:11Z",
"chain_head": "sha256:a3f7e2b1c4d9...", // hash-linked evidence receipt
"motor_version": "caum_v10.31.0"
}
Reviewable exposure as a percentage of spend
| Monthly agent spend | Scenario exposure | Monthly exposure | Annualized exposure* |
|---|---|---|---|
| $562 | 5% | $28 | $337 |
| $10,000 | 5% | $500 | $6,000 |
| $50,000 | 5% | $2,500 | $30,000 |
| $100,000 | 5% | $5,000 | $60,000 |
*Scenario math only. CAUM reports reviewable structural exposure. Realized savings require customer-owned controls and a before/after baseline. Use the planner for your parameters ->
Zero-semantic boundary: CAUM is designed to ingest tool labels, structural metadata, counters, timestamps, and hashes rather than code content, file contents, prompts, payloads, PII, or business data. Customers should validate integrations against their own retention and data-access policies.
Start with a pilot analysis
Upload a sample trajectory file from your production agent environment. Get an observation-only structural PDF report with loop/stagnation evidence, cost exposure, and cryptographic receipts. First analysis free with code PIONEER.
For custom deployment, on-prem options, or volume pricing: contact@caum.systems