AI Integration & AI Product Development in New York.
RAG pipelines and autonomous LLM workflows built into your product. Mojo Studio delivers ai products for founders and businesses in New York, senior engineers only, weekly demos, full IP ownership.
Built right,
shipped fast.
We integrate production-grade AI into real products — custom RAG pipelines over your own data, autonomous LLM agent workflows, and semantic search, built with the same engineering rigor as the rest of your stack. This isn't a chatbot bolted onto a landing page; it's AI wired into your actual product logic, with the guardrails to keep it from hallucinating in front of customers.
Built for New York's market.
NYC's fintech, ad-tech, and enterprise SaaS companies operate on tight product cycles and increasingly treat India-based engineering as a way to run two overlapping shifts — a US product/design team by day, an India engineering team picking up work as New York sleeps — rather than a one-for-one contractor swap. Local NYC dev salaries and the cost of hiring inside a notoriously expensive real-estate market make an India-based studio's rates compelling for founders bootstrapping past their first fintech or media-tech MVP. New York's finance-adjacent industries also mean compliance, security, and polish expectations run high, so studios need a demonstrable track record with production-grade fintech or consumer-facing apps to win trust here.
New York's fintech & trading and media & ad-tech businesses have specific needs when it comes to ai products — this is the local context that shapes how we scope every New York engagement, not a generic playbook applied everywhere.
From brief to launch.
Use-case scoping — where AI actually adds value vs. hype
Data pipeline & vector store architecture
Model integration (OpenAI, Gemini, Claude, or fine-tuned)
Evaluation, guardrails, and production monitoring
AI Products FAQ.
Grounded retrieval (RAG) over your actual data, tight prompt scoping, output validation layers, and explicit fallback behavior when the model isn't confident — hallucination is a design problem, not something you patch after launch.