AI Design Engineering

We turn your data into platforms that think.

Products we build and operate. Services we deliver for companies with data they can't use yet. Two practices, one engineering mindset.

28+
Years building
5
Live platforms
6 weeks
Idea to production
🧠

Six weeks. Fixed scope.
Production at the end.

Most AI consulting projects fail because the scope grows mid-flight. We commit to a tight 6-week loop with a working system at the end — not a prototype, not a deck.

Discovery

Walk your data. Pick the highest-leverage queries. Lock the scope and acceptance criteria in writing.

Foundation

Ingest pipeline, schema, embeddings, retrieval. First end-to-end query running on real data.

Iteration

Tune retrieval, harden extraction, layer guardrails. Daily demos so you see progress, not promises.

Integration

Wire into your stack — SSO, your DB, your existing portal. On-prem if your data demands it.

UAT

Your team uses it on real work. We fix what they hit. No surprises on handoff day.

Handoff

Documentation, runbooks, 30-day support. You own the code, the model choices, and the costs.

Engineering-first,
since 1997

Digital Waterhouse is a design engineering studio focused on AI-powered platforms. We connect messy real-world data — scanned PDFs, decades-old ERPs, sprawling CRMs — to clean, intelligent interfaces that the people doing the work can actually use.

Our products practice proves the approach: we build and operate our own platforms daily, making real decisions with real money on tools we've engineered from scratch.

Our services practice applies that same discipline to client work: fixed-scope engagements that ship production AI systems in weeks, not quarters.

28+
Years building software
5
Platforms in production
6 wk
Fixed engagement scope
Multi-M
Client revenue served
Paul Littleton, Founder & Engineer at Digital Waterhouse
Founder · Engineer

Paul Littleton

The 90s for me were motion-capture films and online entertainment platforms — visual and interactive technical work back when both fields were still inventing themselves. I kept building web platforms through the 2000s. In 2011 I joined Omnivalve and helped scale the business: operations, systems, sales tooling, customer-facing portals — all the unglamorous infrastructure a manufacturing company needs to grow.

That mix of perspectives turns out to be useful. I've been on the buyer side of consultants, the engineer side, and the operations side that has to live with whatever ships. Digital Waterhouse is what happens when you point that range at current AI capabilities. I run my own platforms in production daily, so when I tell a client what works, I'm telling you from yesterday's incident review — not from a Twitter thread.

Let's build something intelligent.

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