AI Models & Serving Infrastructure

AI Infrastructure

Production infrastructure connecting models to operational reality.

Deploying high-throughput model inference, dynamic provider routing, embedding pipelines, vector retrieval engines, and evaluation guardrails across hybrid GPU and cloud environments.

Multi-Model Architecture

Deploying and orchestrating across frontier LLMs, proprietary model APIs, and specialized runtimes to match the highest-precision model to each specific workload.

Production RAG Pipelines

High-accuracy retrieval engines with semantic chunking, re-ranking, and deterministic citation assembly.

Operational Cost Control

Optimize token consumption, implement aggressive caching, and balance frontier reasoning with lightweight local models.

Security & Guardrails

Enforce input/output validation, PII redaction, and strict API access controls across all model interactions.

What we offer

01High-Throughput Model Serving — vLLM, TensorRT-LLM, and accelerated inference platforms
02Dynamic Model Routing & Fallbacks — Latency, cost, and availability-aware routing across frontier providers
03Vector Search & Retrieval Engines — Hybrid search, embeddings, and context assembly pipelines
04Evaluation Harnesses & Guardrails — Automated scoring, safety boundaries, and regression suites
05Private Model Deployment — Secure on-premise and private cloud inference configurations
06Telemetry & GPU Observability — Token consumption, latency percentiles, and error tracking

Pricing

Inference & Model Infrastructure

From $15,000

Start dates and delivery windows are confirmed after scope review.

  • Serving stack architecture & deployment
  • Model routing & fallback pipeline
  • Evaluation harness & observability setup
  • Latency & cost optimization audit

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