A GPU observability and attestation platform that detects jitter, stutter, thermal drift, perceptual stutter, and scheduler interference — and produces a signed receipt the customer can verify. 485/485 tests passing. Stripe checkout, Ed25519 device licensing, dashboard, and export verifier shipped.
The Optimizer agent runs alongside your GPU workload, samples the surfaces that traditional monitoring misses, and produces a continuous signed attestation. The 9-step mocked Stripe end-to-end trace covers checkout, license issue, device binding, cap enforcement, and receipt export.
Per-kernel timing variance against the rolling baseline. Catches the noisy-neighbor case, the bad driver update, and the slow PCIe lane before customer-visible latency moves.
Frame-to-frame and step-to-step stutter with a 9-field signature. The detection signature is the subject of an in-flight provisional patent (Bundle 2, to be filed within 14 days).
Junction temperature, hotspot, and memory-thermal tracking with a predictive horizon of 500ms to 2 seconds. Surface the throttle before it lands.
Weber-Fechner 0.10 threshold applied to user-perceptible jitter. The stutter that the customer will report is the one that gets flagged — not the one that's only visible in a flamegraph.
15.6ms timer-tick interference detection. The cross-process and cross-VM contention that classical GPU monitoring is blind to becomes a first-class detected event with a signed receipt.
The Optimizer ships with Stripe checkout, Ed25519-signed per-device licenses, a 5-device cap enforced at the agent, a dashboard, and a receipt-export verifier the customer can run independently. The 9-step mocked Stripe end-to-end has passed. The detection signature is patent-pending under Bundle 2 of the current provisional batch.
The differentiator between you and the next hyperscaler is provable tail latency. Ship Optimizer alongside your GPUs and turn your noisiest customer's complaint into a verifiable receipt.
Microsecond stutter is money. The 9-field stutter signature plus scheduler-interference detection map directly onto the latency budget that the trading desk already negotiates with infrastructure.
Per-customer attestation that the GPU they paid for is the GPU they got. Receipt-export verifier means the customer can prove the SLA to their own auditor without trusting you.
The Optimizer was built against the named neocloud, HFT, and inference-host buyer profiles where tail latency is contractual.
421 Rust + 64 Python = 485 tests, plus a 9-step end-to-end Stripe trace.
$ cargo test --workspace
Finished test [unoptimized + debuginfo] target(s) in 12.34s
Running unittests src/lib.rs
test result: ok. 421 passed; 0 failed; 0 ignored
$ pytest cloud/tests/ -v
collected 64 items
...
============================ 64 passed in 3.18s ============================
$ python scripts/e2e_mock_customer.py
Step 1/9: create-checkout PASS
Step 2/9: webhook.session.completed PASS
Step 3/9: license issued (Ed25519) PASS
Step 4/9: 5 devices register (1→5/5) PASS
Step 5/9: 6th device DENIED (cap) PASS
Step 6/9: deactivate fp[0] PASS
Step 7/9: 6th retry SUCCESS PASS
Step 8/9: verify license PASS
Step 9/9: export receipts (ZIP) PASSVerified live: Stripe checkout → license issuance → Ed25519 device binding → 5-device cap enforcement → receipt export. All 9 steps pass.
Pilot programs available for GPU hosts and latency-bound inference operators. Includes agent deployment, Stripe + Ed25519 licensing setup, dashboard onboarding, and a customer-facing receipt-verifier demonstration on your live workload.