RAG, chat, and document workflows on your data
AI product work
AI SaaS development for startups
Integrate AI into a product you already run, upgrade a live system, or build a new AI-native SaaS — with production reliability, not a demo reel.
Three ways we do AI work
Integrate: add assistants, search, or document understanding to an existing app using LLM APIs and RAG. Upgrade: add agents and automation to the system you operate today, incrementally. Build: take a new AI SaaS from architecture through billing and launch. We will tell you if a feature is not worth an LLM.
What “production” means here
Eval-able prompts, retrieval that cites real sources, tool permissions you can audit, and fallbacks when a model fails. We integrate frameworks founders already ask for — including Hermes Agent, LangGraph, CrewAI, OpenAI Assistants, and MCP — only when they fit the product.
Who this is for
Early-stage teams that need AI in the product, not a slide. If you already have users, we start with an audit of the current system so we do not rewrite what works.
Agents and automation inside existing SaaS
New AI-native apps with web, mobile, and billing
MCP and agent-framework integration when it is justified
Frequently Asked Questions
Will you use our existing models and vendors?
Yes. We work with the APIs and clouds you already pay for when that is the right constraint.
Do you train foundation models from scratch?
That is rarely the first step for a startup. We start with APIs, retrieval, and product UX. Custom training is a later conversation if the data justifies it.
Is this the same as the homepage AI section?
This page is the dedicated offer. The homepage introduces the three paths; here we spell out scope, constraints, and how engagement works.
Related
Tell us what you want to ship
Email a short brief. We will reply with a practical remote plan — scope, timeline, and whether we are the right fit.