AI Engineering & Integration

LLMs that work in production, not just in demos.

Most AI proofs-of-concept fail in production for the same three reasons: latency, cost, and reliability. We design AI systems with all three in mind from day one — not as an afterthought when the demo starts breaking under real load.

60%

reduction in API costs after prompt optimization

< 800ms

p95 latency on a RAG pipeline serving 10K users/day

4 weeks

from spec to production on a document intelligence system

What we deliver

RAG pipeline design and implementation
LLM integration (OpenAI, Anthropic, Gemini, open-source)
Multi-agent orchestration (LangGraph, CrewAI, custom)
Vector database setup and query optimization
AI feature integration into existing products
Cost modeling and token optimization
Streaming responses and real-time AI interfaces
Evaluation frameworks and quality benchmarks

Our approach

Model-agnostic

We don't have a preferred vendor. We pick the model that fits your latency, cost, and privacy requirements. Sometimes that's GPT-4o. Sometimes it's a locally-hosted Llama.

Evaluation first

We write evals before we write features. If we can't measure quality, we can't improve it. Every AI system ships with a benchmark so you can track degradation over time.

Production-aware

Token costs, streaming latency, rate limits, fallback behavior — we design for the production environment, not the notebook. Your AI feature should work the same on day 1 and day 1000.

Frequently asked

Which LLM providers do you work with?

OpenAI, Anthropic, Google (Gemini), Mistral, and self-hosted open-source models via Ollama or vLLM. We pick the model that matches your cost, latency, and data-privacy requirements — not the one with the best marketing.

Can you integrate AI into an existing product?

Yes. Most of our AI work is additive — adding AI features to products that already exist. We design the integration to be non-disruptive and testable before it hits production.

How do you handle hallucinations and reliability?

Structured outputs, retrieval grounding, evaluation pipelines, and guardrails. We build evals before we ship, so reliability isn't a guess.

Do you work on AI products end-to-end?

Yes — from the model layer through the API to the frontend. You don't need to coordinate three different contractors.

Ready to ship AI that actually works?

Describe your project and we'll respond within 24 hours with a direct assessment — not a sales pitch.

Get in touch