AI features that actually ship
We build practical AI into real products: LLM features, chatbots that know your content, document extraction and workflow automation. Grounded in your data, tuned for cost and speed, and built to make it to production.
AI that does real work
Not a chatbot for the sake of it. Features that save your team time or give your users something genuinely useful.
LLM features in your product
Summaries, drafting, classification, search and other language features built right into your app.
RAG over your own data
Retrieval-augmented generation so the AI answers from your documents and data, accurately, not from guesswork.
Chatbots & assistants
Support and internal assistants that actually know your content and resolve real questions on their own.
Workflow automation
AI that takes repetitive work off your team: triage, tagging, routing, data entry and follow-ups.
Document & data extraction
Pull structured fields out of messy PDFs, emails and documents, turning unstructured text into clean data.
Connect AI to your systems
Wire models into your existing tools and APIs so the output lands where the work actually happens.
From idea to something in production
A grounded process that keeps AI projects out of the demo graveyard and gets them in front of real users.
Find the right use case
We start from a real problem, not the hype. The goal is something that saves time or makes money, not a demo.
Build & integrate
We build the feature and wire it into your product and data, with the right model for the job and the budget.
Ground it in your data
RAG and good prompting keep answers accurate and on-topic, so the AI is useful instead of confidently wrong.
Ship & improve
We get it into production, watch how it behaves with real users, and tune it for quality, cost and speed.
The hype is easy. Shipping is the job.
We treat AI as a tool to solve a problem, built and integrated properly, not a buzzword to bolt on.
It actually ships
Plenty of AI projects stall at the demo. We build features that make it to production and get used, not science experiments.
Grounded in your data
We lean on retrieval and your real content so answers are accurate and trustworthy, which is what makes AI safe to put in front of users.
Cost and speed aware
We pick models and patterns that fit your budget and latency needs, instead of reaching for the most expensive option by default.
Full-stack, not bolted on
We're a full product team, so the AI feature fits cleanly into your app, your backend and your workflows.
Tools we build AI with
AI integration, answered
Can you add AI to our existing product?
Yes. Most of our AI work is exactly that: building a feature and integrating it into a product that already exists, rather than starting from scratch.
How do you stop the AI from making things up?
We ground answers in your own data using retrieval-augmented generation, add guardrails and validation, and design the feature so the model works from real content instead of guessing.
Which models do you use?
Whatever fits the job. We work with OpenAI and Anthropic Claude among others, and choose based on quality, cost and speed for your specific use case rather than a one-size-fits-all answer.
Will this get expensive to run?
It doesn't have to be. A big part of doing this well is choosing the right model and pattern for each task, so you pay for the quality you need without overspending on every call.
We're not sure what AI could even do for us. Can you help?
Absolutely. We're happy to look at your workflows and product and point out where AI would genuinely help, and just as importantly, where it wouldn't.
Have an AI idea worth shipping?
Tell us what you're trying to do. We'll tell you honestly whether AI is the right fit, and if it is, how we'd build it.
Start a project