services

What We Build

Four service areas, all focused on production. Built for startups that need to move fast without accumulating debt that comes back to bite them.

RAG & Retrieval Systems

RAG pipeline development · retrieval augmented generation consultant

Who this is for

Startups building search, Q&A, document intelligence, or any product where an LLM needs to answer questions from a knowledge base.

What we deliver

Document ingestion pipeline (chunking, embedding, vector store)
Hybrid search implementation (semantic + keyword)
Re-ranking layer for retrieval precision
Generation with source citation and hallucination controls
Evaluation harness with recall and accuracy benchmarks
Observability: query tracing, latency monitoring, cost tracking

common starting point: You have a RAG prototype. It works in testing but hallucinates or performs poorly on real queries. We diagnose and rebuild the retrieval architecture for production.

Multi-Agent Systems

multi-agent AI development · LangGraph consulting

Who this is for

Startups building autonomous workflows, research pipelines, or multi-step AI processes that require coordination across tasks.

What we deliver

Agent architecture design (supervisor, sequential, or parallel patterns)
Tool integration and validation
State management and memory across agent runs
Error recovery, retry logic, and graceful degradation
Monitoring and observability for agent behavior

common starting point: You've built agents that work in a controlled environment but fail unpredictably in production or with edge-case inputs. We harden the architecture and add production reliability patterns.

LLM Infrastructure

LLM systems engineering · inference optimization · cost controls

Who this is for

Startups with LLM features in production who are hitting performance, cost, or reliability issues at scale.

What we deliver

Inference cost optimization (caching, batching, model routing)
Latency optimization for real-time and streaming use cases
Rate limiting, circuit breakers, and failover for LLM API calls
Token budget management and cost controls
Scalable async job queues for non-real-time LLM workloads

common starting point: Your LLM features are live but costs are climbing, latency is inconsistent, or reliability under load isn't where it needs to be.

AI Architecture Consulting

AI architecture consulting · LLM systems engineering agency

Who this is for

Teams about to start a major AI build who want to get the architecture right before committing to an implementation path.

What we deliver

2–4 week engagement
Architecture document: system design, technology selection, data flow, integration strategy
Risk identification: where the system is likely to fail and why
Build plan: phased implementation roadmap with clear milestones

common starting point: You're about to hire engineers or hand off an AI project to your team. You need an architecture you can trust before you commit.

Ready to build?

Book a 30-minute call. We'll get a feel for what you're building and where the real engineering challenge is. Just an honest conversation to see if we're the right fit.

Book a Discovery Call