For teams self-hosting image, video or language models
Faster, cheaper GPU inference. Measured, not guessed.
We write inference runtimes in C++ and CUDA, from the kernels up. In one week we benchmark your pipeline, profile where the time and money go, prototype the biggest wins on your workload and hand you a ranked plan with measured savings.
What you get
- 01Reproducible baseline: throughput, p50/p95 latency, cost per output, GPU utilization
- 02Profile of kernels, memory, precision, batching, I/O and cold starts
- 03Prototypes of the top optimizations on your pipeline, measured against an agreed quality bar
- 04Benchmark scripts and raw results, so you can reproduce every number
- 05A ranked plan: each change with its measured or projected saving, effort and risk
- 06A fixed quote to implement the plan, if you want us to
Right for
- AI startups whose GPU bill grows faster than revenue
- Image and video generation products with latency users can feel
- Teams serving open-weight models on their own GPUs
Not right for
- Products that only call hosted APIs (the AI Feature Sprint is a better fit)
- Training-cluster optimization
How it runs
From kickoff to handoff.
Day 1
Access, environment and a reproducible baseline benchmark.
Days 2–3
Profiling: where the milliseconds and dollars actually go.
Day 4
Prototype the top wins and measure them against the baseline.
Day 5
Report and call: the numbers, the plan and the quote.
Guarantee
No path to 30% savings? Full refund.
If we can't show, measured on your workload and hardware, at least 30% lower cost per output or 30% lower latency at the quality bar we agree on day one, you get a full refund, automatically. You keep the report.
Which hardware and frameworks?
NVIDIA GPUs, both data-center and RTX, from Ampere through Blackwell. PyTorch, diffusers, ComfyUI, vLLM, TensorRT, TensorRT-LLM, ONNX Runtime and custom CUDA.
How is the 30% measured?
Against the baseline we record on day one, on the same or cheaper hardware, at your target load, with output quality checked for parity. We agree the exact metric with you before we start.
Do you need our model weights?
We need to run your pipeline, so yes, in your environment. Nothing leaves your infrastructure, and an NDA is standard.
Who owns the work?
You do, once it's paid for. Everything lives in your repository from the first commit, and nothing is locked to us.
Other offers
AI-App Rescue Audit
A senior audit of your Lovable, Bolt, Replit, Cursor or v0 app, with a fixed quote to fix it.
$1,490 · 72 hours
AI Feature Sprint
One production AI feature, in your product, in 10 business days. Fixed price.
$8,500 · 10 business days
Agency Partner Capacity
Senior engineers under your brand, for the AI, backend and GPU work your clients ask for.
$8,000 · 65 senior hours per block