// TECHNOLOGY
A software-to-hardware pipeline purpose-built for inference. Material speed-ups on the GPUs you already own, bit-exact outputs, and a path to custom silicon when inference volume justifies it.
Concrete outcomes your infra, finance, and product teams can measure in production.
20–45% speed-up on current-gen NVIDIA GPUs, workload dependent. No new accelerator purchase required.
Lossless. Same model, same outputs — no accuracy trade-off, no quality regression, no requalification.
Works with your existing checkpoints. No architecture changes, no fine-tuning, no requalification cycle.
Integrates with standard AI serving stacks. Days to deployment, not weeks.
Meaningful reduction in per-inference energy and cost-per-operation — the savings compound at scale.
When inference volume justifies it, the pipeline extends to custom hardware designed against your actual workload shape — without building a full hardware team.
Whether you're serving tokens, frames, or sensor data — the pipeline adapts to the shape of your inference.
Higher throughput and lower latency for production LLM serving
Text-to-image and text-to-video at interactive speeds
Low-latency transcription and streaming audio pipelines
Real-time perception and decision-making under tight power budgets
Deterministic, reliable numerical behavior for regulated workloads
Exact accumulation for simulation, risk, and modeling
Workload-specific benchmarks, integration guides, and architecture briefings are shared under NDA. Tell us your workload and we'll show you what it looks like on our pipeline.
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