OBSERVING
Structural Observation Infrastructure

Structural observation
for autonomous agents.

CAUM is a structural observation layer. It detects loops, stagnation, and wasted compute in autonomous agent execution — without reading your prompts or payloads.

$ caum analyze trajectory.jsonl
# Processing 2,847 state transitions…
✓ Regime: LOOP — Severity T4
✓ Vault: Artifact_Vault_a7f3c2e1.zip
✓ SHA-256: e3b0c44298fc1c14…
Validated at Scale
0
State transitions analyzed
0
Deterministic results
0
Bytes of semantic data read
Ed25519
Cryptographic signatures
Core Capabilities

Observe. Classify. Attest.

CAUM does not steer or evaluate your agent. It classifies the structural behavior of execution and produces deterministic, verifiable results.

Structural Regime Detection

Classifies agent execution into discrete structural regimes — Explorer, Grind, Stagnation, or Loop — through proprietary analysis. No semantic interpretation required.

Cryptographic Attestation

Every analysis produces a deterministic Artifact Vault containing Merkle roots, SHA-256 canonical hashes, and Ed25519 digital signatures. Independently verifiable by any third party.

Zero Semantic Access

CAUM never reads your prompts, API payloads, or proprietary data. It processes only abstract structural coordinates — discrete state identifiers and transition timestamps. Your data remains yours.

Observation Model

Structure reveals what semantics cannot.

Autonomous agents often fail silently: repeated calls, circular plans, and long runs with zero structural progress. CAUM detects these patterns by evaluating trajectory structure at the level of state transitions and structural continuity. No access to reasoning, prompts, code, or data is required.

  • Terminate looping agents before they exhaust compute budgets
  • Audit historical agent failures with mathematical evidence
  • Maintain strict data privacy — only abstract coordinates processed
  • Classify behavior into Severity Tiers (T1–T5) for automated enforcement
Structural Regime Analysis Sample Output
Explorer
T1
Grind
T2
Stagnation
T3
Loop
T5
Processing Pipeline

Five steps. Fully deterministic.

Identical input always produces identical output. No stochastic models. No probability estimates. No model drift.

1
Upload
Submit a JSONL trajectory file with discrete state transitions.
2
Canonicalization
Data is parsed and normalized into the canonical structural format.
3
Structural Analysis
Proprietary classification of trajectory dynamics and structural regime assignment.
4
Classification
Each trajectory window is assigned a Structural Regime and Severity Tier.
5
Report & Vault
PDF observation report and cryptographic Artifact Vault are generated.
Data Flow

Minimal input. Maximal proof.

What You Provide

A minimal dataset containing only discrete state identifiers and timestamps. No private user data. No API keys. No proprietary code.

  • State coordinate (opaque hash or identifier)
  • Transition sequence index
  • Timestamps (ISO 8601)
// sample_trajectory.jsonl {"step": 1, "state": "a3f8c2", "ts": "2026-01-15T08:41:02Z"} {"step": 2, "state": "b7d1e0", "ts": "2026-01-15T08:41:03Z"} {"step": 3, "state": "a3f8c2", "ts": "2026-01-15T08:41:05Z"}

What You Receive

A deterministic, independently verifiable report detailing the structural regime of the trajectory, with a cryptographic Artifact Vault.

  • Structural Regime (Explorer, Grind, Stagnation, Loop)
  • Severity Tier (T1–T5) per observation window
  • Structural Observation Report (PDF)
  • Artifact Vault (ZIP) — Merkle roots, SHA-256, Ed25519
Deployment

Integrate on your terms.

Forensic

Offline Analysis

Analyze historical trajectory datasets. Generate institutional structural observation reports for post-incident investigation and compliance audits.

  • Batch JSONL processing
  • Offline deterministic execution
  • Air-gapped compatible
Best for root-cause analysis and regulatory compliance.
Live

Real-Time Monitoring

Integrate CAUM into running systems. Receive structural regime classifications and Severity Tier alerts as agents execute.

  • Low-latency REST API
  • Webhook stagnation alerts
  • Cloud-managed infrastructure
Best for continuous monitoring of autonomous agents.
Enterprise

Embedded SDK

Deploy CAUM directly within your infrastructure. Full local control. Zero external data transfer.

  • Native Python & Go bindings
  • Zero-telemetry architecture
  • Bare-metal execution
Best for sensitive or high-volume deployments.
Output

The Structural Observation Report

A strictly formatted PDF designed for institutional audits, compliance reviews, and forensic root-cause analysis. Every report includes canonical cryptographic commitments, ensuring mathematical verifiability.

No sensitive context is ever exposed. Reports contain only structural regime classifications, severity assignments, and cryptographic attestations.

Structural Observation Report
Ref: CAUM-2026-0742
Date: 2026-02-15
Dataset Hashe3b0c44298fc1c14…96fb924
Net RegimeLOOP — Severity T4
VerificationDeterministic — Artifact Vault attached
Steps 0–14: Explorer regime. Healthy structural expansion.
Step 15: Structural recurrence detected. Regime transition.
Steps 16–40: Closed-loop trajectory. Terminal state confirmed.
Trust Architecture

Independently verifiable.

Every report ships with a canonical SHA-256 commitment, Merkle root, and Ed25519 signature. Results are reproducible offline from the Artifact Vault.

Live Demonstration

Watch CAUM observe.

CAUM performs structural observation on a simulated execution, detects anomalies, and generates verifiable attestations — all without accessing semantic data.

Observer Idle
START END OBSERVING
Phase I
Detection
Phase II
Attestation
Phase III
Resolution
Structural Observer
CAUM initiates read-only structural observation. The system classifies execution behavior through state transition analysis without accessing underlying payload data.Privacy guarantee: Semantic data is never processed.
Evidence Stream
Resources

Research & Formal Documentation

Run structural analysis on your dataset.

Upload a trajectory. Receive verifiable evidence of your agent's structural behavior.