Why we built Statistiq
The AI services market is bifurcated. Strategy firms over-staffed with associates. Offshore engineering shops under-staffed with senior judgment. Statistiq exists in the seam between the two.
We spent the last decade-plus inside enterprise AI teams. We shipped systems inside a Top-3 global consulting firm. Inside a Fortune-100 retailer. Inside venture-backed AI startups across insurance, healthcare, retail, and marketing.
We saw the inside of the work. We saw what makes the difference between a slide and a system in production. We saw the moments where strategic clarity collapsed into execution mush, and where execution velocity outran strategic judgment. The seam between those two failures is where AI investments quietly die.
The bifurcation
The AI services market today is bifurcated.
On one side: big-firm strategy work. Priced for boards. Over-staffed with associates. Beautiful decks. Architecture diagrams that nobody downstream can build from. Risk registers that turn into compliance theatre by the time they reach a model risk officer.
On the other side: offshore engineering shops. Priced for procurement. Under-staffed with senior judgment. Notebooks delivered as if they were products. Pilots that ship and don't survive contact with the buyer's regulator, the buyer's P&L, or the buyer's audit committee.
Between the two is the actual work — strategy that translates to engineering, engineering that survives regulators and P&Ls, operations that compound. Buyers have been frustrated by this gap for years. They've told us. We've been them.
What the 2025–2026 inflection changed
Two things changed in 2025 and 2026 that made the gap untenable rather than annoying.
First, agentic AI moved from prediction to execution. The class of systems we build today doesn't just suggest — it acts. It calls tools, it triggers workflows, it talks to customers. The cost of a wrong answer has changed shape. Generic SI playbooks no longer survive it.
Second, governance moved from afterthought to gating factor. The EU AI Act is in force. State AI laws are proliferating in the US. NAIC model bulletins, FDA AI/ML draft guidance, OCR positioning on AI as a business associate. The era of pretending governance was something you'd bolt on after launch is over.
The buyer-side patterns we kept seeing — pilots that don't ship, governance that arrives too late, vendors who can't defend their own architecture to a regulator — became existential, not annoying.
Statistiq, in the seam
Statistiq is the firm we wished existed when we were on the buyer side.
We are senior practitioners — operators, not pure-strategy consultants and not body-shop engineers. We work in five industries where our team has direct, shipped experience: insurance, healthcare, life sciences, retail, and marketing. We are building flagship products in insurance and healthcare. We engage senior-to-senior, build production-grade, and stay through to operations.
The three things we organize around:
Strategy & Advisory — Decide what AI to build, and whether it will move a number. Roadmaps, deep-dives, investment cases, governance setup, build-vs-buy reviews. Outcomes engineering-credible enough to fund.
Build & Engineering — Design and ship the systems. Production-grade. ML systems, GenAI applications, agentic workflows, data foundations, AI product engineering. Senior teams. No offshore handoff.
Run & Optimize — Keep the systems in production. Monitoring, MRM, evals, retraining, optimization, AI CoE support. The compounding work — where 95% of programs break and we step in.
What we won't do
We won't deliver a notebook and call it a model. We won't deliver a Figma mock of a dashboard and call it a system. We won't staff a project with one senior and three associates and call it senior-led. We won't write a roadmap whose first milestone is another strategy phase. Every Build engagement ships to production or we don't take it.
We are intentionally a small firm, and we intend to stay that way. We grow only with senior practitioners who can ship on day one — no associate pyramids, no offshore handoff, no "delivery center" between scoping and shipping.
Receipts, not claims
Where prior-employer confidentiality permits, here is some of what our founding team has shipped:
- A SKU-store-week recommendation system across 3,000+ stores at a Fortune-100 retailer, ~82% per-store precision, 14% annual on-hand improvement.
- AI-driven patient triage on GCP / Vertex AI inside a Top-3 consulting firm's healthcare practice, 12% lift in patient onboarding efficiency, 85% recall on triage likelihood.
- Multi-agent submission digitization, RAG pipelines for risk insight, and carrier-grade MRM at a venture-backed insurance AI platform.
- Scalable time-series forecasting on AWS and RAG-based recommendation on LangChain at a venture-backed SaaS marketing platform, 7% annual TCV increase.
- NLP-driven process mining at a Top-3 consulting firm's banking practice, 95% classification accuracy.
We don't list these to flex. We list them so a buyer on the other side of an inbox can decide whether we've actually walked the rooms they walk.
If you're sizing an AI roadmap, choosing a vendor, building a system, or operating one that needs to stay alive — we'd like to hear about it. Most first conversations are 30 minutes with a senior partner from Statistiq, not a sales development rep.