CAUM Agent Evidence Layer

Audit-ready structural evidence for agent work.

CAUM sits beside AI agents and turns every run into a private-content-safe evidence receipt: structural health, loops, review boundaries, policy effectiveness, token exposure, and cost exposure without reading raw prompts, code, files, or customer payloads.

Start Evidence Pilot Run PDF Receipt See Policy Effectiveness
Zero-content Observe-only No blocking No compliance certificate claim No guaranteed savings claim
Agent Evidence Pack
Evidence ready
Structural logging
available
Review readiness
active
Policy delta
observed
Raw content
not used
pack: caum.agent_evidence_pack.v1.0 | decision: observe_only | allowed_to_block: false

Tracing shows what happened. CAUM shows whether work stayed structurally healthy.

Agent teams are starting to collect traces by default. The missing layer is evidence: did the run keep converting into progress, where did it become reviewable, and did the policy you added actually reduce structural exposure?

Evidence receipts

Each run gets a structural receipt with hashed identifiers, health tier, review boundary, trace quality, and exposure fields.

Policy effectiveness

Compare customer-marked before/after cohorts to see whether retry ceilings, handoff limits, or exit contracts reduced reviewable exposure.

Governance readiness

Map structural evidence to logging, human review, and post-deployment monitoring workflows without presenting CAUM as a legal certificate.

The layer that goes between agents and accountability.

CAUM does not replace LangSmith, Langfuse, OpenTelemetry, logs, or your agent framework. CAUM consumes structural telemetry from those systems and returns evidence that a buyer, operator, or reviewer can understand without reading private content.

Claim lock: CAUM supports evidence readiness. It does not certify legal compliance, judge semantic truth, predict all failures, or stop agents.
1
Bring one workflowUpload JSONL, OpenTelemetry-style events, LangSmith/Langfuse exports, Claude Code traces, or a simple event list.
2
Generate a baseline receiptCAUM reports structural health, loops, stagnation, trace quality, review boundary, and observed exposure.
3
Apply a customer-owned policyThe team adds a retry ceiling, handoff limit, tool budget, review gate, or reasoning-to-action exit contract.
4
Measure the after stateCAUM compares before/after cohorts and reports observed structural exposure deltas, not guaranteed savings.

What the Evidence Pack contains

The output is intentionally narrow. CAUM gives teams enough structural evidence to review agent operations, improve policies, and support governance conversations without exposing sensitive content.

Evidence area CAUM output Boundary
Structural loggingRun-level record of event classes, counters, hash ids, profiles, tiers, and review signals. Evidence receipt No raw prompt, code, file, document, or customer payload required.
Human review readinessPassive review boundaries, hard alerts, review-only tiers, and policy triggers. Review pack CAUM recommends review; it does not decide or block.
Post-deployment monitoringLoops, stagnation, exact cycles, work conversion, token exposure, and cost exposure over time. Live monitoring Observed exposure, not a realized financial reduction claim.
Policy effectivenessBefore/after comparison after the customer applies a policy to the workflow. Policy ledger Observed structural delta, not ROI proof or compliance certification.

Start with one workflow. Leave with evidence.

The fastest monetizable path is a CAUM Agent Evidence Pilot: one workflow, one baseline, one policy, one before/after evidence pack. If recurrence matters, move that workflow into CAUM Live.

Start Evidence Pilot Run PDF Receipt