We test AI with your real data and business needs, then build it when we know it will work, so you don’t waste time and money on AI that doesn’t.
Real systems for real businesses, from a designer sock brand in New York to immigration law practices.
Four AI systems running behind one store.
I need a gift for my dad. He likes bold, classic patterns.
Khan and Nami suit that well. Both come in the two-pair gift box, ready to give.
Khan
Nami
Where is my order? And can I exchange it for a larger size?
It shipped today and arrives within 3 business days. Exchanges are free, so I’ve started one for size L.
A tiled medallion pattern in turquoise and cream, drawn from the same carpet traditions as the rest of the collection.
The work behind the store, automated.
Orders, stock, returns and customer updates move on their own, and your team only sees what needs a person.
From intake to evidence, with an attorney in the loop.
Client intake, documents and case evaluation in one system, every finding traced to its source and reviewed by an attorney.
Five randomized trials, 622 law students, three model generations. Speed gains replicate cleanly. Accuracy gains mostly don’t.
Aug 16, 2026 · 12 minResearchWhat the controlled evidence actually shows about information, representation and outcomes.
Aug 14, 2026 · 38 minResearchWhat the ABA, EOIR and a dozen state bars require of immigration attorneys using AI, read from the primary documents.
Aug 12, 2026 · 8 minResearchWhat eight controlled studies actually show, once you check the numbers instead of the narrative.
Aug 11, 2026 · 21 minWe do not use customer data to train public AI models, and we do not enable model training on customer data with any third-party provider we use.
Data handling, access control and vendor terms are all specified before implementation, so you know exactly where your data goes and how it’s used.
Clear sources, role-based access, testing, auditability, human review, documentation and escalation paths, where high-risk work needs them.
No. Research is the starting point. When the evidence supports a solution, we design and build the production system around the organization’s data, users, workflows and governance requirements.
Systems where reliability, traceability and real-world performance matter: knowledge and research systems, workflow automation, document intelligence, decision support, customer operations and internal AI-enabled tools.
Yes. We evaluate an organization’s data sources, software, permissions and processes early, then design around those constraints, rather than asking a team to reshape its work to fit a generic tool.
A focused conversation about the workflow, the decision or task you want to improve, the data involved, the people who use it, and the cost of getting it wrong. From there we recommend a research engagement, a feasibility evaluation, a pilot, a production build, or a non-AI alternative.
Bring us the problem. We’ll tell you honestly whether AI is the right answer.