Services
Models that run on your hardware.
We make models smaller, faster, and cheaper to serve — quantization, distillation, and inference optimization that move you off the metered endpoint.
- Quantization and distillation
- Inference optimization
- Deploys on your own hardware
Deliverables
What you walk away with.
Engagements end with artifacts on your side of the table — not a dependency on ours.
A smaller model that holds up
Quantization and distillation tuned until the compressed model matches the baseline where it matters.
A faster serving path
Batching, caching, and runtime work on the stack you actually serve from — not a benchmark rig.
Proof against the baseline
Side-by-side evals of quality, latency, and cost, shipped with the harness that produced them.
How it works
Four steps, no mystery.
Every engagement runs the same visible arc — you can see where you are from day one.
Baseline
Profile the model and the target hardware; fix the quality bar the optimized model must clear.
Compress
Quantize and distill toward the footprint the hardware wants.
Optimize
Tune the serving path end to end — runtime, batching, memory.
Validate
Quality, latency, and cost measured against the baseline before anything ships.
The meter stops — inference lives on hardware you control.
Get started
Bring the problem — we'll bring the lab.
Tell us where you are and where the run needs to land — we'll scope the engagement and put researchers on it.