Forward-deployed AI engineering
We make AI work where it actually runs.
DataTranquil embeds engineers inside your team and builds the system in production — not in a slide deck. The model was never the hard part. Everything after it works is.
Engagement · run record
- 01Discovery
- 02Pilotlive
- 03Embed
Each phase is authorized separately.
More than 25 years of hands-on enterprise data and AI delivery.
What we do
Three lines of work, one practice.
Most AI programs do not fail on the model. They fail on the data underneath, the workflow around it, and the handover after the demo. We work all three.
Line 01
AI Strategy
Where AI is worth applying, and where it is not. Readiness, opportunity mapping, and an honest sequence — not a transformation deck.
Line 02
Implementation
Forward-deployed engineering. We build and ship the system embedded in your team, against real workflows — discovery, pilot, embed.
Line 03
Data & Analytics
The unglamorous foundation. Getting the data in shape — pipelines, quality, structure — before any model is allowed near production.
What is forward-deployed engineering?
Forward-deployed engineering means our engineers embed inside your team and build the AI system where it will actually run — against your data, your workflows, and your edge cases. The work ships into production with your people, rather than arriving as a report you then have to implement alone.
How engagements run
Discovery, pilot, embed.
No open-ended discovery, no six-month strategy phase. Each phase is scoped on its own and ends with your decision about whether the next one happens.
- 01
Discovery
We embed briefly and map where AI is worth applying — and, just as important, where your data actually is and what shape it is in. You decide whether to build, defer, or stop.
- 02
Pilot
We build one real thing end-to-end against a real workflow, against success criteria agreed before the build starts. Not a demo that works in a controlled room — the version that survives a Tuesday afternoon. You decide whether it goes to production.
- 03
Embed
We ship it into production inside your team and hand over the operating knowledge, so it keeps working after we step back. You own it from there.
What is the relationship between DataTranquil and VexioHQ?
Both are Data Tranquil Inc. DataTranquil is the consulting and engineering practice — we deliver AI inside client teams. VexioHQ is our product brand: a production AI system we build and operate ourselves, handling live calls and booking real appointments. Running our own production AI is how we keep the delivery practice honest — we carry the same uptime, integration and failure-handling problems we are hired to solve.
We are our own first client
This site was built under the discipline we sell.
AI drafting produces confident claims nobody can substantiate — the same failure mode we are hired to guard against. So this site ships behind a claims lint that blocks any unsupported statement from reaching a page, and an independent reviewer that reads the work before it ships. The run-records are public.
claims lint · this repo
$ npm run lint:claims
✓ clean (0 findings)
Start here
Find out what is worth building — before you build it.
A fixed-scope AI-readiness discovery — one candidate use case, a look at your data and workflow, and a plain recommendation at the end. Priced on a short expert call.