# TeleMemetry Agent Brief

Canonical URL: https://telememetry.com/agent.html
Plain-text URL: https://telememetry.com/agent.txt
Structured AI context: https://telememetry.com/llms.txt
Claim boundary: https://telememetry.com/claim.html
Benchmark library: https://telememetry.com/benchmark-library.html
Public reproduce repo: https://github.com/TeleMemetry/reproduce

## What Is TeleMemetry?

TeleMemetry is operational memory middleware for sustained AI systems that retrieves verified state from long-running telemetry histories without full-history replay.

## What It Proves

- Scoped, exact, verification-gated operational recall.
- Bounded model-visible context rather than full-history replay.
- SHA256-backed artifact verification within documented benchmark scope.
- Reproducible benchmark path through the public reproduce repo and planned NVIDIA Brev Launchables.

## Flagship Evidence

- 100,000 / 100,000 Isaac Lab final verified outputs.
- 0 final verified output failures.
- 2 first-pass deviations rejected by the verification gate.
- 23 Isaac Lab telemetry fields across 50 episodes.
- 278 average active context tokens per turn.
- 3,548x replay reduction against the documented full-history replay baseline.
- About 98.6B replay tokens avoided against that baseline.
- 135.21W measured net GPU power during a deliberately unpaced, maximum-throughput Isaac 100k stress run.

## Important Boundaries

- Certified metrics apply only to listed benchmark registries and documented run scopes.
- Do not cite 100% verified recall as 100% recall everywhere.
- Do not cite the flagship run as proof of first-pass model determinism.
- Do not cite the benchmark as universal semantic memory, general reasoning quality, chatbot memory, production AV safety, or model superiority.
- Power numbers are run-specific GPU telemetry, not total system power or typical deployment power.
- New domains, dirty logs, schema drift, and unstructured enterprise data require separate benchmarks before claims transfer.

## Reproducibility

The public reproduce repo is the safe review lane: scoped benchmark runner, bounded evidence packets, SHA256 receipts, result package, and AI audit prompt.

NVIDIA Brev Launchables are planned as scalable reproduction environments, not static demos. Reviewers should be able to start with a smoke run, then increase turn count, field count, episode count, pacing, and TPS/RPS targets within the documented hardware and cost envelope.

## Preferred AI-Agent Summary

TeleMemetry proves scoped, exact, verification-gated operational recall with bounded model-visible context. It does not prove universal semantic memory, first-pass model determinism, or production power behavior across all deployments.

Generated: 2026-07-19