AI product engineering from architecture to scale. We build AI-powered products with the rigor of software engineering and the intelligence of modern AI, including production pipelines, evaluation systems, guardrails, and monitoring. Not AI experiments. Engineered AI products.
Proof-First Delivery
What We Offer
Each module is designed as a production block with integration boundaries, governance hooks, and measurable outcomes.
Design AI-native product architectures from scratch. Model selection, pipeline design, data flow, caching strategy, cost modeling, and scaling plan. Architecture decisions backed by production experience, not blog posts.
Production LLM pipelines with RAG retrieval, tool use, structured outputs, streaming, and error handling. Claude, GPT-4, and open-source models with intelligent routing. Pipelines that work at 3 AM with no engineer watching.
User interfaces designed for AI interactions. Streaming response rendering, confidence displays, inline editing of AI outputs, feedback collection, and error states. Next.js and React Native frontends that make AI feel natural.
Automated evaluation pipelines that measure AI output quality continuously. Benchmark suites, regression detection, A/B comparison, and production quality dashboards. You cannot improve what you do not measure.
Deploy AI products with zero-downtime, auto-scaling, cost monitoring, and self-healing. CI/CD pipelines with evaluation gates — code that degrades AI quality does not reach production.
Take AI products from 100 users to 100,000. Caching layers, queue-based processing, model routing for cost management, database optimization, and infrastructure scaling. Engineering for growth.
Delivery Proof
Selected engagements that show architecture depth, execution quality, and measurable business impact.
Delivery Advantages
Design AI-native product architectures from scratch. Model selection, pipeline design, data flow, caching strategy, cost modeling, and scaling plan. Architecture decisions backed by production experience, not blog posts.
Production LLM pipelines with RAG retrieval, tool use, structured outputs, streaming, and error handling. Claude, GPT-4, and open-source models with intelligent routing. Pipelines that work at 3 AM with no engineer watching.
User interfaces designed for AI interactions. Streaming response rendering, confidence displays, inline editing of AI outputs, feedback collection, and error states. Next.js and React Native frontends that make AI feel natural.
Automated evaluation pipelines that measure AI output quality continuously. Benchmark suites, regression detection, A/B comparison, and production quality dashboards. You cannot improve what you do not measure.
FAQ
Tell us about your product vision — we'll design an AI architecture and propose a team that gets you from concept to production with engineering rigor.