← All services
DISCIPLINE 03 · AI ENGINEERING

Custom AI,
not glued
GPT.

yourmodelRAGEVALAGENTFT
OpenAI · AnthropicLlama · Qwenpgvector · QdrantModal · Replicate

If your AI roadmap is "wrap a chatbot around our docs" — please call literally anyone else.

We build production-grade AI features and full agentic systems. RAG with hybrid retrieval and citation traceability, fine-tuned small models for high-volume tasks, agent orchestration with structured outputs and proper retries.

Every AI feature ships with an evaluation harness. We measure quality, regress on changes, and publish numbers — even the embarrassing ones.

  • RAG system (hybrid search · reranker · citations)
  • Fine-tune + serving infra (Llama/Qwen)
  • Agent / multi-step workflows
  • Eval harness + observability dashboard
  • Internal AI tools / custom GPTs
Typical scope6–14 wks
AI projects22 shipped
Avg. eval gain+34%
Brief us on AI work →
How it unfolds
AI that you can actually measure.
01
Week 1–2
Problem Framing
We define the use case precisely, map data sources, and write the first eval set before touching any model. No problem definition, no engagement.
02
Week 3–5
Prototype & Baseline
First working system against the eval harness. Baseline numbers documented. We iterate until the numbers actually mean something.
03
Week 6–12
Production Build
Fine-tuning, RAG pipelines, or agent orchestration — whichever the problem demands. Observability, tracing, and latency budgets from day one.
04
Week 13+
Deploy & Monitor
Staged rollout with eval regression testing on every deploy. We hand off a system you can debug and improve without us.
From the studio
We've seen companies spend $200k on AI features that made their product worse. Every single time, the root cause was the same: no evals. If you can't measure it, you're just guessing — and guessing with language models is expensive.
AnishFounder · Vedwix
Ready to build?

Real AI, not
demo-ware.

Brief the studio