Greenfield AI products
Mobile and web products where AI is the experience: recommendation engines, generative interfaces, conversational products, multi-agent applications.
Service
AI Product & Platform Engineering
Production AI products and SaaS platforms, built to scale.
Greenfield AI products and SaaS platforms with AI built into the architecture from day one: observability, fallback paths, eval frameworks, multi-tenancy. Built by senior engineers who've shipped at venture scale.
Where we focus.
Six application areas where this service ships measurable results, chosen against the failure modes most growing businesses hit.
SaaS platforms
Multi-tenant SaaS with AI integrated where it adds value. Rails, Node, Python, Go backends with React or Next.js frontends. Cloud-agnostic deployment.
Vertical AI platforms
Domain-specific AI products for fintech, healthcare, legal, real estate, built with the industry's data shapes, compliance, and integrations in mind.
Multi-agent applications
Coordinated AI agents that plan, retrieve, write, and verify across systems. Built with explicit handoff points, structured outputs, and per-agent eval suites.
AI-first data platforms
Data lakes, vector stores, semantic search, and feature pipelines designed for AI workloads from the start, not retrofitted into a traditional warehouse.
Multi-tenant AI SaaS
Per-tenant isolation for prompts, data, and evals. Usage-based pricing instrumentation, customer-level model routing, and tenant-aware audit trails.
Related work
Where we've shipped this in production.
FINTECH · YC S20 · $30M raised Volopay
First production version of a YC S20 fintech operating across six countries. Engineering partner through scale.
Read case study -> B2B PROCUREMENT · MULTI-AGENTRacepoint
Multi-agent LLM SaaS that collapses B2B procurement into a natural-language workflow.
Read case study -> EVENT DISCOVERY · UKSumwhere
Greenfield event-discovery product built end-to-end: discovery, scoping, build, and launch.
Read case study ->FAQ
How is this different from adding AI to an existing product? +
If you have an existing product, see AI Integration. This service is for greenfield builds: new products where AI is central to the architecture, not retrofitted. Different infrastructure decisions from day one.
What's the typical timeline from idea to launch? +
First production version in 12-16 weeks. Larger products with multiple AI features run 4-6 months. Working prototype in week 4-6.
Will you tell us if our idea won't work? +
First milestone is a scoping deliverable that pressure-tests the idea. If something looks off, we tell you in week 2 rather than week 12.
Who owns the IP and AI assets? +
You do. All code, prompts, evals, fine-tuned models, and configurations belong to you on milestone payment.
What does a typical build engagement look like? +
Scoping in week 1-2, working prototype by week 4-6, V1 to production in 12-16 weeks. Larger multi-feature builds run 4-6 months across 2-3 production releases. Milestone-based with go/no-go reviews at each step, you keep the option to stop or pivot.
Tell us what you're solving for.
We'll listen first, ask the right questions, and follow up with a clear proposal.