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AI consulting and development · Salt Lake City, UT

AI consulting and development for Salt Lake City companies

Your AI pilot answers well in the demo, and nobody can yet say what it'll cost a month or whether this week's change made it better. Our senior engineers take it to production with retrieval that cites its sources, an eval on every change and a model bill you can forecast. Utah's industrial banks and Lehi's software companies ask for that first, and so do the health systems around the University of Utah.

Founded

2017, and still independent

Bench

115+ engineers, 80 Databricks-certified

Experience

Fifteen years average, per engineer

Serving

Salt Lake City, Provo, Lehi, Ogden

A substantial fintech and software base along the Wasatch Front, a large integrated health system beside it, and an unusually high share of companies still run by their founders. If that's you, you want the AI system in production and its operating cost known, without a transformation programme in front of it.

DatabricksTemporalAzure

TechFabric is a Databricks partner with an award-winning Databricks engineering team, 80 of them Databricks-certified, and a Temporal partner. Where a system reaches past the workspace we build on Azure, AWS and Google Cloud.

What ai consulting and development covers

Agents that hold state

A task that runs for three days, calls six systems and waits twice on a person cannot live in a request handler. We build agents on a durable runtime, so a deploy in the middle of a run does not lose the run, and a retry does not send the same email twice.

Retrieval that cites what it used

An answer nobody can trace is an answer nobody can defend. Retrieval is built so every response carries the documents behind it.

Evaluation, before and after

Without a score, every prompt change is a matter of opinion. We put deterministic scorers and model-based judges in front of the thing so a change ships with a number attached rather than with a feeling.

Human approval where it belongs

Some actions should stop and wait for a person. That gate is part of the system rather than a policy document, so an agent that wants to issue a refund pauses, the approval is recorded, and the run picks up where it left off.

Cost you can see

Model spend, retrieval infrastructure and the review time a system still needs are the numbers that decide whether it stays live after the first quarter. They get instrumented at build time, not discovered on an invoice.

Governed data access

An agent reads through the same grants a person would. On Databricks that is Unity Catalog, so a model that tries to reach a table it has no grant for fails the way any principal fails, rather than because the prompt asked it nicely.

AI consulting in Salt Lake City

Founder-led companies from Lehi to downtown Salt Lake want AI consulting that ends in something running, and a regulated pilot may qualify for Utah's AI Sandbox. We spend the first weeks choosing one use case with a measurable return, building it with an evaluation that shows whether it works, and stating the monthly cost before you commit.

The first enterprise deal brings the questionnaire

Plenty of software and fintech companies between Salt Lake City and Lehi are still run by their founders, and the first large customer usually arrives with a security questionnaire and a SOC 2 Type II requirement. A fintech partnering with one of Utah's industrial banks, chartered by the state's Department of Financial Institutions, gets a second list on top, because the bank's examiners expect it to oversee its vendors.

Most founders treat that as a compliance project for after the build, and they lose two quarters to it. We'd rather the platform produce its own evidence from day one. Access reviews come from the grant tables, change history from the deploy pipeline, and the audit log is written by the system, so the questionnaire turns into a document exercise and the Type II window opens on something already running.

Your stack gets read against the Trust Services Criteria your auditor will test, and we mark which controls the platform can evidence by itself. Single sign-on with role-based access goes in first, then a single pipeline for every production change, then log retention long enough to cover the observation period. The product roadmap keeps moving beside it.

Clients we have done this for

If your application database has quietly become your warehouse, read how TotalLoop moved. It started as a cloud-native platform on Azure with its own CRM and a sales dashboard, and later moved off Cosmos DB and SQL Server onto Databricks Lakebase, converted with TechFabric Airlift and cut over in reversible waves.

B2B ecommerce

DealerIQDealerIQ

TotalLoop finds a dealership's customers with equity in their vehicle and matches them to cars on the lot. DealerIQ brought the idea and the dealership know-how, and our senior engineers worked inside its team to build it on Azure, test it with one dealer account and ship a lean first version. Later we moved it off Cosmos DB and SQL Server onto Databricks Lakebase, in waves that could each be rolled back.

Also for

  • Verizon
  • Location Services
  • SRS Distribution

How an engagement runs

  1. 01

    Two weeks, fixed fee

    An AI Readiness Assessment reads what you already run, names the use cases that will survive your data and your permissions, and puts a number on what each will cost to operate. It ends in a written document that is yours either way.

  2. 02

    One system, named

    We pick the first thing to build with you and say what done looks like before starting. A first system that reaches production beats three that reach a demo.

  3. 03

    Build it with your team

    Your engineers are in the repository with ours from the first week. The pattern has to be one they can extend after we leave, which does not happen if they meet it at handover.

  4. 04

    Run it, then hand it over

    We stay on the pager while it settles, because the design decisions look different when the person making them is the one being woken. Handover happens when it is boring, not when the invoice is due.

Two weeks, fixed fee, and a written plan whether or not you build it with us.

Tell an engineer what you want to build

A senior engineer reads it and replies within one business day, usually with the questions that decide the first two weeks.

A sentence or two is plenty, such as what it should do and what stands in the way today.

Goes straight to a senior engineer. By sending this you agree we can contact you about your enquiry, and occasionally about our work. Tell us to stop at any time and we will.

Around Salt Lake City

The state's own AI calendar

Utah's state government hosts its own AI conference. The Utah AI Summit, put on by the State of Utah with Nucleus Utah, fills the Grand America Hotel on 8 December with breakouts on government, the workforce and healthcare. The University of Utah's One-U Responsible AI Initiative runs a consortium outside organisations can join, and MLOps and AI Utah meets monthly in Lehi for the engineering side.

The state also regulates AI directly. Its Office of Artificial Intelligence Policy, part of the Utah Department of Commerce, runs an AI Sandbox where a company, the office and the relevant regulator agree how one rule applies during a limited pilot. A regulated pilot may qualify, and if yours might, read what the office has published before the build is scoped, since an evaluation that scores every change is the evidence it'll want.

Map of the Salt Lake City-Murray metro area2 counties: Salt Lake County; Tooele County. The lighter shape is Salt Lake City city, and the red dot marks downtown Salt Lake City.

The Salt Lake City-Murray metro area. Utah: Salt Lake and Tooele counties.

Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.

  • Meetup · Monthly, usually the last Tuesday evening

    MLOps and AI Utah

    Talks lean toward implementation over research, so it's a good place to hear how Lehi teams monitor a model once it's serving real customers.

    Volunteer organisers. Pattern, 1441 W Innovation Way, Suite 500, Lehi.

  • Conference · 8 December 2026

    Utah AI Summit 2026

    Hosted by the state itself, the summit is where you'll hear how Utah's government and its healthcare breakout think about AI before any rule reaches you.

    State of Utah and Nucleus Utah. Grand America Hotel, Salt Lake City.

  • University · Ongoing, with events through the academic year

    One-U Responsible AI Initiative, University of Utah

    Outside organisations can join the initiative's community consortium, which gives a regulated company a route to university researchers working on fairness and evaluation.

    Scientific Computing and Imaging Institute, University of Utah. Warnock Engineering Building, University of Utah.

  • Meetup · Monthly, usually the third Wednesday evening

    Utah Data Engineering Meetup

    Every AI system depends on the pipelines feeding it, and the evenings alternating between Recursion and Vivint are where Utah's pipeline builders compare notes.

    Volunteer organisers, part of Forge Utah. Alternates between Recursion, Salt Lake City, and Vivint, Lehi.

  • User group · Several events a year, plus DevFest SLC each September

    GDG Salt Lake City (Google Developer Group)

    For teams already on Google Cloud, these evenings on Gemini and generative AI show what the platform does well and where you'd still build your own evaluation.

    Google Developer Groups volunteers. Venues vary, including Salt Lake City Public Library, 210 E 400 S.

More in Salt Lake City (5)
  • KubeCon + CloudNativeCon North America 2026

    The North American edition of the CNCF's cloud native conference, covering Kubernetes, platform engineering and cloud native infrastructure, with co-located events around it.

    9 to 12 November 2026. Salt Palace Convention Center, 90 S West Temple, Downtown.

  • SALT: Software Aficionados Learning Together (formerly Utah Java Users Group, UJUG)

    Formerly the Utah Java Users Group, a nonprofit meeting since 1999, now usually at Lucid Software in South Jordan, with free monthly talks on Java, software engineering and AI.

    Monthly, Thursday evenings. Lucid Software, 10355 S Jordan Gateway, South Jordan.

  • Salt Lake City Python (SLCPython)

    A monthly Python group for working and aspiring programmers, meeting early in the evening at The Shop co-working space on 400 South or a county library.

    Monthly, usually the first Wednesday evening. Rotates between The Shop, 350 E 400 S, and Salt Lake County libraries.

  • BS in Data Science, Kahlert School of Computing, University of Utah

    An undergraduate data science degree from the Kahlert School of Computing, teaching students to build and use software tools for data analysis and data-based decisions.

    Ongoing degree programme. University of Utah, Salt Lake City.

  • Salt Lake City R Users Group

    An R user group for Salt Lake City and the University of Utah community, mixing technical talks online with social gatherings in person.

    Every one to two months. Talks online; socials around Salt Lake City, such as Millcreek.

Each listing was checked on its organiser's own page on 12 October 2026. Dates and venues move, so the link is the source.

FAQ

AI consulting and development in Salt Lake City: common questions

Do you work with Salt Lake City companies?

Yes, and with companies across the United States. Arizona does not observe daylight saving, so from November to March we are on the same clock as you and from March to November we are an hour behind. The working day overlaps almost completely.

Do you have an office in Salt Lake City?

The office is in Gilbert, Arizona, with teams in Amsterdam, Dnipro and Hyderabad. Delivery is remote or hybrid, and we travel for discovery, workshops and the opening weeks of a build.

We are founder-run and our first big customer wants SOC 2.

Then the useful thing is a platform that already produces the evidence, so the questionnaire becomes a document exercise. We would rather get one system into production with the trail built in than run a compliance programme alongside a build.

What kind of AI development do you do?

Agents that carry state across a long task, retrieval that cites what it used, workflow automation that survives a restart, and the evaluation that tells you whether any of it got better. The common thread is that it has to run unattended and be explainable afterwards, which is a different problem from getting a good answer once.

How does an AI engagement start?

Usually with something short and fixed so the cost is known before you commit. The AI Readiness Assessment runs two weeks for a fixed fee and ends with a written deliverable that is yours whether or not you continue.