AI consulting and development · Denver, CO
AI consulting and development for Denver companies
When data arrives faster than your engineers can read it, an AI pilot that can't cite its source never reaches production. We put senior engineers on it, not a handoff team, to build retrieval that cites the record it read, agents that keep their state and evals that score every change. Denver's satellite builders and the telecom networks run from Englewood and Broomfield live with that volume, and a homebuilder meets it more slowly.
Founded
2017, and still independent
Bench
115+ engineers, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
Denver, Boulder, Aurora, Lakewood
Aerospace, telecommunications and energy, with an outdoor and endurance sport industry that's a genuine sector here rather than a lifestyle note. If your data comes from satellites, networks, wells or athletes, it arrives at a volume where the model's answer has to cite what it read.
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 Denver
AI consulting in Denver often starts with more data than anyone can read, from spacecraft telemetry out of Littleton and Centennial to well data from the DJ Basin. We decide where retrieval can answer questions with citations, where export rules limit what a model may see, and which use cases to build first.
Export rules decide who reads the data
United Launch Alliance is headquartered in Centennial and Lockheed Martin Space builds satellites in Littleton, and their suppliers across the Denver metro hold export-controlled technical data. Under ITAR and the EAR, letting a foreign national read it counts as an export, even in an office on the Front Range. State administers one regime and Commerce the other, so table access is a legal question first.
Most data platforms grant access by role and project, and that's where export control breaks. A role says what someone does, while ITAR asks who they are, so access has to turn on attributes such as US person status and authorisation, resolved when the query runs. Copying controlled tables into a separate workspace feels safer, and then quietly drifts out of date.
We ask your export compliance team to classify the data before any pipeline runs, then encode each classification as a governed tag in Unity Catalog and write the policy against the tag. Nothing ships until a test shows an unauthorised account seeing nothing it shouldn't, and that test runs again every time the schema changes.
Clients we have done this for
Endurance sport runs on results from many timers and race organisers, and Athlinks needed more than 400 million athlete records from disparate sources stitched together. A Temporal pipeline with automated retries and real-time visibility does that join, for data that was never designed to meet.
Health & Wellness
Athlinks
Athlinks had more than 400 million athlete records from sources that never agreed on who an athlete was, and a matching run that died halfway through couldn't just start again. Our engineers took the project from prototype to production as a serverless pipeline on AWS with Temporal holding the state. Failed steps now retry on their own, failures reach Slack as they happen, and the matching rules are tuned for each tier.
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 Denver
Denver and Boulder's AI demo circuit
AI Tinkerers runs a Denver-Boulder chapter built around member demos and technical talks, with past sessions on Playwright MCP performance and knowledge graphs for agents, and it has met at Code Talent on Blake Street in RiNo. On 5 December the Applied Machine Learning Collective of the Rockies holds the free Colorado Applied Machine Learning Mini Conference in Denver, covering agents, datasets and model training.
Satellite, network and well data arrive here faster than anyone can read them, which makes citation the feature that matters. An answer that names the telemetry frame or the well log it came from can be checked, and one that doesn't can't be trusted with anything consequential. We build retrieval that cites its source, and the evals that show whether a model change actually helped.
The Denver-Aurora-Centennial metro area. Colorado: Adams, Arapahoe, Broomfield, Clear Creek, Denver, Douglas, Elbert, Gilpin, Jefferson and Park 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 Denver-Boulder
Past sessions on Playwright MCP performance and knowledge graphs for agents tell you the level, which is builders comparing real trade-offs.
AI Tinkerers, Denver-Boulder chapter. Venues vary, including Code Talent, 3412 Blake St, RiNo.
Conference · 5 December 2026
Colorado Applied Machine Learning Mini Conference
Free, practical and run by a regional collective, it covers datasets and model training, the parts of AI work most pilots underestimate.
Applied Machine Learning Collective of the Rockies. Denver, venue announced to registrants.
Meetup · Monthly, usually the second or third Tuesday evening
Denver Data Dudes and Dudettes - Monthly Meetups - Low Key
The group describes itself as a place for connecting rather than selling, and its current focus on LLMs shows what local data teams are trying.
Volunteer organisers. Rotates between Denver-area bars, including New Terrain Brewing in Golden.
University · Degree programme, fall and winter starts
Master of Science in Applied Data Science and Artificial Intelligence, University of Denver
Evening and hybrid classes mean many students already work locally, so it doubles as a way to upskill your own staff.
University of Denver Ritchie School of Engineering and Computer Science. University of Denver campus and online.
User group · Several evenings a month in the autumn, usually Tuesdays
Denver Java Users Group
Meeting since November 1995, the group now covers AI tooling for Java, which matters if your enterprise systems are Java and the agents must call them.
Volunteer organisers. Usually Oracle, 500 Eldorado Blvd, Broomfield.
More in Denver (3)
- ÜberConf 2027
A four-day developer conference with over 150 sessions and workshops across ten tracks, including architecture, modern Java, generative AI, DevOps, Kubernetes and security.
13 to 16 July 2027. The Westin Westminster, 10600 Westminster Blvd, Westminster.
- Colorado Startup Week (formerly Denver Startup Week)
A free week of sessions for founders and technologists, begun in Denver in 2012 and based at The Link on 15th Street, renamed in 2025 when it went statewide. It reports over 250 sessions.
Annual, usually mid-September. The Link, 930 15th St, Downtown Denver, and across Colorado.
- Bachelor of Science in Data Science, University of Colorado Denver
An undergraduate data science degree grounded in mathematics, statistics and computing, taught with the engineering and business schools, with electives in applied fields.
Ongoing degree programme. CU Denver, Auraria Campus, 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 Denver: common questions
Do you work with Denver 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 Denver?
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.
Can you handle ITAR or EAR controlled technical data?
Access control has to be a legal boundary rather than a convenience, which means grants resolve at read time and nothing sits behind the application with broad access. We would want your compliance team to define the boundary and we build the system that holds it.
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 Denver
What else we build for Denver companies.
Software development in Denver
Two dashboards disagree with each other and a spreadsheet disagrees with both, and every fix waits for an engineer you haven't hired.
Databricks consulting in Denver
Your Databricks bill climbs with the data, and governance gets harder when export law decides who may read a table.
AI consulting and development elsewhere
The same work, in other metros. The full list is here.
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