Most "AI developers" have built a demo chatbot in a weekend. We work in RAG pipelines, AI agents, and automation that runs inside real businesses — with the logging, cost controls, and fallback logic a demo never needs. Vetted, NDA-first, and fast to start.
AI features fail quietly — a chatbot that hallucinates or an agent that loops isn't a bug you'll catch in a five-minute demo.
Every engineer has shipped AI features that handle real user traffic, not just a proof of concept that worked once.
You get a defined deliverable and price before work starts — not an open-ended hourly clock on an experimental feature.
Enough working-hours overlap for daily standups and fast decisions, instead of a 12-hour async lag on every question.
Your prompts, data, and model architecture stay yours — signed before any technical discussion starts.
LLM engineers, RAG developers, and AI agent specialists — matched to what your project actually needs, not a one-size-fits-all hire.
A defined scoping call and proposal process instead of a recruiting cycle that takes six weeks before anyone writes code.
Every AI project needs a different mix of skills — here's how we typically staff one.
Retrieval, fine-tuning, and agent orchestration for production-grade AI systems.
Retrieval-augmented pipelines that ground answers in your actual documents and data.
Custom AI chatbots for support, sales, and internal tools — not a templated widget.
Multi-step AI agents that call tools, APIs, and your internal systems.
Custom GenAI features built on OpenAI, Claude, or open-source models.
Custom model training and deployment when off-the-shelf APIs aren't enough.
It depends on scope — a single chatbot integration costs far less than a production RAG system with fine-tuning and monitoring. We give a fixed-scope estimate after a short discovery call rather than a blanket hourly rate.
In-house makes sense once AI is core to your product and you need someone iterating on it daily long-term. For a defined feature or a first AI product, an outside team gets you to production faster without a six-figure annual commitment.
Beyond calling an API: retrieval and embedding design, prompt evaluation, cost and latency tradeoffs, and knowing when fine-tuning is actually worth it versus better retrieval.
Most engagements start within one to two weeks of the scoping call, once we've defined the deliverable and matched the right specialists to your project.
Yes, NDAs are standard before any technical discussion. You own all code, prompts, and models built for your project — no licensing-back arrangements.
Tell us what you want AI to do in your product — we'll scope the right team and a fixed estimate within 48 hours.