◆ SERVICE

Retrieval-augmented generation (RAG) development

Production RAG — chunking strategy, embedding choice, hybrid retrieval, reranking, evals. The 90% that gets ignored when teams stop at "vector DB hooked up".

◆ WHY MIR

Why teams pick us

Senior-only team

Every engineer ships production code. No staffing-pyramid markup, no junior-tax. 9+ years building outsourced product teams for venture-funded clients.

Live products, not slides

JobCannon (B2C SaaS, live), Make It Real Academy, MIR Foundation. We use what we ship and we ship what we sell.

Operators, not order-takers

Our team has built and shipped products end to end. We engineer like operators because we are operators — focused on your outcome, not billable hours.

◆ STACK

What we build with

pgvector / Qdrant / Pinecone OpenAI / Voyage / Cohere embeddings BM25 + dense hybrid Cohere / Voyage rerankers Ragas / TruLens evals
◆ PROCESS

How we ship

  1. Build a 100-question gold-set before touching embeddings.
  2. Baseline with naive retrieval, measure recall@k and faithfulness.
  3. Iterate: chunking → embedding → hybrid → rerank → metadata filters.
  4. Ship with eval CI — every prompt/embedding change is benchmarked.
◆ REFERENCES

Recent work

JobCannon — production AI/SaaS career platform: 1500+ skills, 2500+ careers, multi-locale, payment-grade Stripe integration. Built end-to-end with the same RAG systems stack we'd put on your project.

See live →
◆ THE MAKE IT REAL NETWORK

Build it, or staff it

Engineering is one piece. When you'd rather hire your own team, drive growth, or vet a candidate, the rest of the network runs the same operator playbook.

◆ START A PROJECT

Tell us what you're building

We respond within 24 hours. NDA available on request.