Washington runs on policy, compliance and public service: federal contractors, trade associations, law and lobbying firms, think tanks and health organisations. AI here has to meet federal security standards and hold up to public scrutiny.
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 District of Columbia rules
Regulations we design around
Cloud services sold to federal agencies
FedRAMP
AI features hosted on authorised cloud services, inside the authorisation boundary.
Defence contractors
CMMC
Controlled unclassified information kept inside assessed environments, AI tools included.
Federal agencies and their contractors
OMB M-25-21
Inventories, risk practices and human oversight for high-impact AI.
Healthcare providers, plans and their vendors
HIPAA
Safeguards and a business associate agreement for anything touching patient data.
Anyone holding DC residents' data
DC breach law
Security safeguards and prompt notice if personal data leaks.
Working together · Eastern Time
Working with us from Washington, DC
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.
How do you prevent errors in public-facing documents?
Drafts are grounded only in the sources you provide, every claim is linked, and nothing is published without human review.
Can we keep client and member information confidential?
Yes. We can host models in your own environment and restrict answers to what each user is permitted to see.
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.
