# AI consulting and development in Tampa, FL > Financial services back offices larger than the city's profile suggests, healthcare systems, and a defence contracting base around MacDill. If you run one of those, the work you want automated is the multi-day, multi-system kind, and it has to finish. Canonical: https://www.techfabric.com/ai-development-tampa Serving: Tampa, St. Petersburg, Clearwater, Brandon, Sarasota, Lakeland Headquarters: 1530 E Williams Field Rd, Ste 201, Gilbert, AZ 85295. No office in Tampa. --- ## Why Tampa work is our work Your back-office AI pilot stalls the first time a run waits two days on a person and nobody knows where it stopped. We build agents on a durable runtime, so that run picks up where it left off, with retrieval that cites its source and evals that score every change. Around Tampa that's Westshore's back offices, the hospitals by Tampa General and the defence contractors, and a title company too. ## AI consulting in Tampa AI consulting in Tampa is mostly back-office work, the claims, onboarding and reconciliations of financial firms and the contract paperwork for the commands at MacDill. We trace each process end to end, mark the steps a model can do and the ones a person must, and estimate the hours returned before recommending a build. [AI consulting in Phoenix](https://www.techfabric.com/ai-consulting-phoenix) ## Work a buyer here would recognise Lending and servicing back offices spend their days on multi-step approvals, and Auto Approve's vehicle refinancing ran on that kind of work. The study shows an automated approval engine that doubled monthly loans processed and replaced more than four manual workflows without adding a single agent. ## A back-office process has to finish, and prove it did Tampa Bay carries more financial back office than its skyline suggests. Raymond James is headquartered in St. Petersburg, JPMorgan Chase runs large operations around Tampa, and the health systems and contractors serving MacDill sit beside them. Their work is servicing, claims and reconciliation, where one case crosses several systems over several days and every step can be the subject of an examiner's question. ## Questions ### Our back office is mostly manual. Where do you start? With the process that costs the most when it half-completes. A durable workflow that records every step turns a multi-day, multi-system process into something that survives a restart and produces its own audit trail. Auto Approve is the published version of exactly that. ### Do you have an office in Tampa? 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. ## 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. ## Working with us from Arizona Arizona does not observe daylight saving, so we are two hours behind you from November to March and three hours behind from March to November. That leaves most of your afternoon overlapping our morning, which is usually enough. Most delivery is remote or hybrid. We travel for discovery, workshops and the opening weeks of a build.