Generative AI development for San Francisco businesses
LLM features for San Francisco products and teams, grounded in your own data, evaluated before release and engineered to keep inference costs in check.
San Francisco builds the tools everyone else adopts: SaaS platforms, fintech, biotech and the startups around them. Teams here move fast on AI, so the hard part is rarely the demo. It is evaluation, cost, security review and shipping to real customers.
Answers with sourcesEvery answer links to the document behind it.
Tested before launchAccuracy measured on a test set you agree.
Access follows rolesPeople only see answers from what they may read.
Our work
Projects we've delivered across industries
Real projects for real clients, one case study at a time.
Adding GenAI features into existing web apps, mobile apps, ERPs, and CRMs, such as summarization, content drafting, smart search, and image generation.
Built for California rules
Regulations we design around
Businesses handling Californians' data
CCPA / CPRA
Notice, opt-outs and data minimisation for personal data AI uses.
California employers
CA hiring AI rules
Anti-bias testing and records for AI used in hiring and promotion.
Health businesses in California
CMIA
Stricter-than-HIPAA limits on sharing medical information.
Banks, lenders, fintechs
GLBA Safeguards
A written security program covering every system that handles customer financial data.
Working together · Pacific Time
Working with us from San Francisco
Your early morning is our late evening, so we meet live as your day starts and build while you sleep.
7–9 AM PTLive callReview progress and make decisions together
Your working dayYour feedbackYour team tests and comments in writing
Overnight PTWe buildProgress is ready for your next morning
Want to see how a week with us would look?
Tell us your hours and your project, and we'll plan the live time around your day.
We measure cost per request from the first prototype, then use caching, smaller models for simple steps and tighter prompts, checking each change against the quality tests so savings do not cost accuracy.
Can we switch model providers later?
Yes. We keep the model behind a thin layer with its own tests, so moving between providers is a measured change rather than a rewrite.
What does a generative AI development company do?
A generative AI development company designs, builds and runs AI that writes, answers and summarizes for your business. We build chatbots, knowledge assistants on your own data and GenAI features for your apps, and test them for accuracy before launch.
What does generative AI consulting include?
We help you find the use cases worth building, check whether your data is ready, choose the right models, and estimate cost and timeline. Then we can build the first solution with you, often starting with a 2-week pilot.
Can I hire generative AI developers for my own project?
Yes. You can hire our generative AI developers to build a new solution, or to work alongside your team on one you have already started.
What is RAG and why does it matter?
Retrieval-augmented generation (RAG) finds the most relevant passages in your own content and gives them to the language model with the question, so answers are grounded in your data and can show their sources.
Do we need to fine-tune a model?
Often not. Good retrieval and prompt design solve most business use cases. We recommend fine-tuning only when tests show it clearly improves quality, cost or speed.
How do you keep our data private?
We design around your security rules: private deployments where needed, access control on every answer, no training on your data without your consent, and full logging.
How long does a generative AI project take?
A chatbot or knowledge assistant for one use case usually takes 2 to 4 weeks. Larger solutions across several systems usually take 6 to 10 weeks. We often start with a 2-week pilot.
