AI consulting and development · Austin, TX
AI consulting and development for Austin companies
You shipped an AI feature to win the first enterprise deal, and now it has to hold up in production without engineers babysitting it. We build the durable half, an agent that keeps state across a long task, retrieval that cites its sources, an eval on every change and a model bill finance can forecast. In Austin that's a SaaS company, a semiconductor supplier in Round Rock or a health-tech startup near Dell Medical School.
Founded
2017, and still independent
Bench
115+ engineers, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
Austin, Round Rock, Cedar Park, San Marcos
Semiconductors and software in roughly equal measure, a decade of corporate relocations, and a startup base that has grown into companies with real compliance obligations. If yours is one of them, you've probably shipped an AI feature already and now need it to be durable, measured and affordable.
AzureTechFabric 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 Austin
In Austin the call usually comes after the first AI feature has shipped, from a Capital Factory startup or a company at the Domain. We review what's running, measure its accuracy and cost, and plan how to make it durable and affordable, with the evaluation and governance a first enterprise customer asks about.
Compliance arrives before the security hire
Austin's software companies tend to meet their compliance obligations before they've hired anyone to own them. The first enterprise deal brings a security questionnaire and a SOC 2 request together, and the Texas Data Privacy and Security Act has covered the personal data of Texas residents since 1 July 2024. The state attorney general enforces it, and gives a company 30 days to cure a violation before suing.
Screenshots and a spreadsheet of who approved what get most companies through their first audit, and the spreadsheet gets rebuilt the following year. We think evidence should come from the platform as it runs. Every deploy, grant and read of customer data gets recorded when it happens, so the platform already holds whatever sample the auditor picks, and deciding that up front costs days where retrofitting it costs a quarter.
We list the controls your auditor will test and trace each one to the event that proves it, then wire those events before touching features. Model calls get the same treatment, with the prompt version and cost logged per request, because enterprise security questionnaires have started asking how AI features are governed.
Clients we have done this for
Like many software companies, TotalLoop began as a cloud-native platform on Azure with its own CRM and a sales dashboard. It later moved off Cosmos DB and SQL Server onto Databricks Lakebase, converted with TechFabric Airlift and cut over in reversible waves, the careful way to change a database under a live product.
B2B ecommerce
DealerIQ
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
How an engagement runs
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.
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.
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.
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.
Around Austin
Demo nights from Guadalupe to Brazos
AI Tinkerers Austin runs demo nights every month or two, often around STATION Austin downtown, where local builders show working projects and then take technical questions. Hack AI meets most months on a Thursday evening on Guadalupe Street, a few blocks from the UT campus, and on campus the Machine Learning Laboratory houses the Center for Generative AI and the NSF's Institute for Foundations of Machine Learning.
The UT lab works on foundations and the demos downtown show what runs this week. Your project lives in the duller middle, which is what a run costs, how anyone knew a prompt change helped and who gets paged when an answer's wrong. That middle is what we build, with an eval that puts a number on every change before it reaches your Austin customers.
The Austin-Round Rock-San Marcos metro area. Texas: Bastrop, Caldwell, Hays, Travis and Williamson counties.
Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.
Meetup · Every one to two months, weekday evenings
AI Tinkerers Austin
Downtown demo nights end in technical questions from the floor, where a SaaS team hears how others kept an AI feature up once enterprise customers relied on it.
AI Tinkerers, Austin chapter. Downtown Austin, often around STATION Austin.
User group · Monthly, usually a Thursday evening
CNCF Cloud Native Austin (Kubernetes Austin)
Recent sessions on stateful AI and LLM apps on Kubernetes cover the unglamorous half of an AI feature, where it runs and how it recovers.
Volunteer organisers, an official CNCF community group. Rotates between STATION Austin, Downtown, and the Domain.
Conference · 17 to 18 November 2026 in person, 16 November online
MLOps World and GenAI Summit 2026
Case studies on taking agents into production, from teams who did it, which is the part of the story vendor launches tend to skip.
TMLS, with a volunteer steering committee. Etter-Harbin Alumni Center, Austin, TX.
University · Ongoing
Machine Learning Laboratory, The University of Texas at Austin
Home to the Center for Generative AI and an NSF institute, the lab is a source of research partners and senior hires with depth.
The University of Texas at Austin. University of Texas at Austin campus.
University · Ten months full-time, or 23 months part-time
MS in Business Analytics and Artificial Intelligence, McCombs School of Business, UT Austin
Its students study generative AI and its responsible use in business, so the programme turns out analysts who can judge an AI feature critically.
McCombs School of Business, The University of Texas at Austin. UT Austin campus; part-time online with five Austin visits.
More in Austin (4)
- SXSW 2027
South by Southwest's annual conference and festivals, which include a Tech & AI conference track alongside startup, design and other tracks.
15 to 21 March 2027. Downtown Austin.
- PyTexas 2027 Conference
The annual Texas Python conference. It opens with a tutorial day and a Python Community Leadership Summit, followed by two days of talks.
16 to 18 April 2027. Austin Central Library, Downtown.
- Hack AI
A monthly evening meetup in Austin for people building with AI and machine learning, held a few blocks from the University of Texas campus.
Monthly, usually a Thursday evening. 1705 Guadalupe St, near the UT campus.
- GDG Austin (Google Developer Group Austin)
Austin's Google Developer Group runs in-person sessions on Flutter, Google Cloud and AI tooling for local developers.
Several events a year. Capital Factory, 701 Brazos St, Downtown.
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 Austin: common questions
Do you work with Austin companies?
Yes, and with companies across the United States. Arizona does not observe daylight saving, so we are one hour behind you from November to March and two hours behind from March to November. A morning standup on your clock is still early afternoon on ours.
Do you have an office in Austin?
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 need SOC 2 and our first enterprise security review at once.
A platform that already records who did what, under whose authority and when, turns both from a project into a document exercise. The work is deciding where evidence comes from before the first handler is written, which costs almost nothing then and a quarter afterwards.
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.
Also in Austin
What else we build for Austin companies.
Software development in Austin
The platform your business runs on was written for a company half your size, and the people who wrote it have moved on.
Databricks consulting in Austin
If you bought Snowflake or Synapse early, you may now be paying for a second stack to run AI beside it.
App development in Austin
Your app shipped fast and won real users, and now every release breaks something nobody still on the team wrote, so the launch you promised keeps sliding.
AI consulting and development elsewhere
The same work, in other metros. The full list is here.
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