Supercomputing engineer for your
cloud spend and cheating agents.

Deterministic run profiles for faster, drift-verified production.

Queue a workloadSee caught agent cheats
01 · WORKLOAD BOUNDARY
02 · 9-LAYER CORE
2,748
engine tests
108 ULP gate
03 · VERIFIED PROOF
● PASS · Ed25519 receipt
NVIDIA Inception Amazon Web Services Microsoft HP OpenAI U.S. Department of Defense

Member of the NVIDIA Inception program · Partners with AWS, Microsoft, HP and OpenAI · Active federal contractor for the U.S. Department of Defense

2,748 engine tests passing · 0 failures · Ed25519-sealed receipts
Calibrate your run (zero chat · 24h turnaround)Which bottleneck above is closest to your current stack?
1. Multi-node CPU/MPI stall (1.32×) →2. GPU cloud spend (851× MI300X / T4) →3. Catch cheating agents (0.000 gate) →Drop run log →
Three ways to verified production

A 1% drift is fine in a chatbot.
In physics, it breaks the law.

Option AHiring Your Own $200k Engineer + Coding AI
Time to production
3 to 6 months
Hardware memory
1 to 2 GPUs
Numerical gate1,091 bins slip
Who signs off
One generalist
Option BExternal Gig Marketplaces & Legacy Agencies
Time to production
12 to 24 weeks
Hardware memory
0 records
Numerical gateSpot checks
Who signs off
Rotating taskers, no stake
Computelab.coComputelab.co 9-Layer Engine + Principal Partners
Time to production
24 hours
Hardware memory
2,748 engine tests
Numerical gate1,091 to 4 bins108 ULP · ΔE ≤ 0.01% · 0.1354 Å
Who signs off
95% Automated Engine · 5% U.S.-citizen Principal Architects, critical judgment and sign-off
Six domains

Where generalist tools stop.

From production run to owned AI

We run the production work today, and turn it into the training environment you own tomorrow.

While our 9-Layer Engine and Principal Architects deliver a production workload, every step, solver tolerance, and blocked shortcut is recorded into an executable training environment. Customers and AI labs train models on real solver and silicon ground truth across Gymnasium, OpenEnv, Harbor, and Prime Intellect verifiers. Five registered environments and three in final checks, 108 adapter test functions.

Environment 01gpu-kernel-gym
CUDA / ROCm / Triton Kernel VerificationMulti-round GPU kernel synthesis and optimization gated against 0xFFFFFFFF poison buffers, async device-timer returns, and 108-ULP float64 reference bounds.86.3898 ms to 0.1015 ms on MI300X · 108 ULP gate
Environment 02crash-model-certification
Solver response matrix17-run OpenCourant matrix across thread/rank counts and parallel arithmetic switchesOracle: 1.0 · Noop: 0.0 · Cheats ≤ 0.50
Environment 03md-gpu-migration
CPU-to-GPU migration339,695-atom OpenMM migration held within 0.1354 Å RMSD14.3x speedup
Environment 04quantum-circuit-compilation
Compilation under budgetsChemistry circuits compiled under error, qubit, and Toffoli budgets with mHa accuracy gatesOracle: 1.0 · 21 seeds · 14 cheats ≤ 0.37
Environment 05atlas-speedup-program
Baseline accelerationAccelerating CAE, LC-MS, and power-grid baselines under strict numerical invariantsOracle: 1.0 on 8/8 seeds · worst cheat: 0.37
Environment 06upstream-breakage
Live recoveryRecovery of pinned scientific and GPU workloads broken across 301 monitored upstream library and SDK releases301 upstream releases monitored
Final checksautomotive-program
Multi-department programMulti-department vehicle program with cross-department driftOracle: 1.0 on 60 seeds · Noop: 0.0 · all cheats ≤ 0.30
Final checksclinical-course
Regulated progressionRegulated clinical study progression with deterministic state checksOracle: 1.0 on 40 seeds · all cheats ≤ 0.35
Final checksfinance-close
Enterprise close45-day enterprise finance close under a 650-step budgetOracle: 1.0 in ≤ 413 steps · all cheats ≤ 0.46
Calibration Benchmark: 0 of 9 frontier-model runs scored 1.0 · 0 of 48 open-weight episodes passed the 0.95 bar · 1,176 cheat rollouts across 56 planted cheats capped at ≤ 0.50.
The 9-Layer Engine

Nine layers, from board bring-up to distributed systems.

Layer 01

Board bring-up

Checks how firmware, drivers and runtimes work together on a new board.

Read the engine
The model

Machines do 95%.
Principals sign the last 5%.

9-Layer Automated Engine
95% automated. Trace matching, poison-buffer and ULP gates, root-cause isolation.
5% human. U.S.-citizen Principal Architects for critical judgment and sign-off.
Verification

Every run ships with a receipt you can check offline.

SHA-256 manifest, Ed25519 key, FP64 tolerance.

computelab · replay of recorded runsType a command








  
Run on verified bare metal.

  

    
Self-serveProduction workload and verification sprintFixed price per workload. 24-hour automated baseline diagnosis, cross-silicon kernel or solver optimization, and an offline-verifiable Ed25519 proof pack.Deploy a workload

    
Enterprise and defenseDedicated enclave for regulated teamsCustom contract, CAGE 25LV8. Air-gapped, VPC, or on-premise deployment inside your security boundary, with U.S.-citizen Principal Architects for critical judgment and sign-off.Talk to a Principal

  






  15-second check
  
What are you checking first?

  
A. Multi-node scalingB. GPU kernel latency & ULP driftC. Pre-tapeout FPGA/RTL ProtoVal