New York runs on regulated, document-heavy work: onboarding clients, pricing risk, handling claims and managing leases. It is where AI has the most work to do, and the highest bar for control.
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 New York rules
Regulations we design around
Banks, insurers, DFS-licensed firms
Part 500
Access controls, MFA and audit trails on every system AI touches.
Anyone holding New Yorkers' data
SHIELD Act
Reasonable safeguards for the private data AI systems read and write.
Hiring for NYC roles
Local Law 144
Bias audit and candidate notice for tools that score or rank candidates.
Healthcare providers, plans and their vendors
HIPAA
Safeguards and a business associate agreement for anything touching patient data.
Working together · Eastern Time
Working with us from New York
Your morning is our evening, so we meet live at the start of your day and build while you sleep.
8–10 AM ETLive callReview progress and make decisions together
Your working dayYour feedbackYour team tests and comments in writing
Overnight ETWe 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.
Can we use generative AI with data covered by the SHIELD Act?
Yes, with safeguards. We keep private data inside systems you control, limit what the model can see by role, and log access, which are the kinds of reasonable safeguards the SHIELD Act expects.
Is AI-drafted content safe for regulated New York firms?
It can be, with review built in. Drafts go through your compliance or legal reviewers before anything is published, and the tool keeps a record of who approved what.
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.
