AI inference, ten ways.
Each one shipped.
We don't ship anything that hasn't passed the same eval suite as the hosted baseline.
AI Infrastructure Migration
From OpenAI, Anthropic, Together, Replicate, Bedrock, or Vertex onto your own GPUs in your VPC. We design the cutover plan, run shadow traffic, validate eval parity, and stage the rollout behind feature flags so customers never notice.
Inference Optimization
Speculative decoding, paged attention, INT8/FP8 quantization, kernel fusion. We profile your actual production traffic, then commit to a target, p95 latency, tokens/sec, $/1M, and ship until we hit it.
Custom CUDA / Triton kernels
When the off-the-shelf doesn't fit. Fused ops for unusual attention variants, sparse MoE routing, novel KV cache layouts, custom samplers. Profiler-led, math-first.
GPU Hardware advisory
What to buy, when to rent, when to colo. We've sized clusters from a single workstation to multi-thousand-GPU H200 fleets. Vendor-agnostic, we have no resale agreements.
Inference Scaling & Autoscaling
Multi-region deployment, request routing, cold-start mitigation, traffic shaping. Built on what you already run, k8s, Nomad, bare metal, not a proprietary platform.
RAG Performance Tuning
End-to-end retrieval pipelines that don't blow your latency budget. Embedding model choice, vector store sizing, hybrid retrieval, reranker placement, batching across stages.
Model Distillation & Quantization
Take a 70B teacher down to a 7B student that holds eval parity within tolerance. INT4/INT8/FP8, GPTQ, AWQ, LLM-QAT, whatever the hardware likes best.
On-prem / VPC Deployment
Air-gapped, ITAR, HIPAA, EU data residency, whatever your compliance regime requires. We deploy and document everything; your team operates it.
SRE & On-call (limited)
Three-month bridge contracts only. We share on-call rotation while your team learns the system. Then we leave, on schedule.
Cost audit
Written diagnostic. We inspect your stack, model your spend, and tell you in writing how much you'd save self-hosting. Refundable against the engagement that follows.
How we measure.
Real workloads, real traffic
Numbers from actual production rollouts, sampled across the day. Not synthetic stress tests.
Eval parity before perf
We don't quote a speedup unless the model passes the same eval suite as before, within the agreed tolerance.
Hardware disclosed
Every benchmark says exactly which SKU, how many, what interconnect, and what the host OS was running.
Failures included
We publish the cases where it didn't work, too. The interesting margin is in what doesn't optimize.
Not sure which one you need?
The cost audit usually answers it, refundable against whatever comes next.
Start with an audit →