AI development · Portland, OR
AI development for Portland companies
Portland is athletic and outdoor apparel headquartered along the west side, semiconductor manufacturing in Hillsboro that gave the corridor its Silicon Forest name, and a consumer brand base that sells worldwide from one metro.
Founded
2017, and still independent
Bench
115+ people, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
Portland, Beaverton, Hillsboro, Lake Oswego
Consumer brands here want AI in the product catalogue, the supply chain and the customer conversation, and each of those touches data about a person. We build agents bounded by the same permissions as their user, with retrieval that cites its source, so the brand can say what the system knew and why.
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 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.
Clients we have done this for
Funko's commerce and warehouse systems are a consumer brand at global scale, from the storefront to the pick list. The same shape as the brands here.
Warehouse management
Funko
A warehouse management system built to cut operating expense, reduce reliance on manual work, and double throughput efficiency.
Consumer data carries the rules now
The Oregon Consumer Privacy Act took effect in 2024 and a brand selling nationally answers to California's as well. A system that can say what it holds about a person, delete it on request and prove both is cheaper to build than to retrofit, and that is a data model decision rather than a policy page.
None of that is unusual for Portland, and none of it is a reason to build slowly. It is a reason to decide where the evidence comes from before the first handler is written, because the alternative is reconstructing it later from logs that were not designed to answer the question.
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.
Headquarters
1530 E Williams Field Rd, Ste 201Gilbert, AZ 85295
Phone
+1 (480) 681-6806Also
Amsterdam, Dnipro, Hyderabad
Working hours
Portland business hours, most days
FAQ
AI development in Portland: common questions
Do you work with Portland companies?
Yes, and with companies across the United States. Arizona does not observe daylight saving, so from March to November we are on the same clock as you and from November to March we are an hour ahead. Either way the working day overlaps almost completely.
Do you have an office in Portland?
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 build a consumer platform that satisfies state privacy laws?
Yes, by making the data model answer the questions the laws ask: what we hold about a person, where it came from, who has read it, and how it is deleted.
Access resolves at read time through the catalogue, the event trail shows every use, and a deletion request is a workflow that finishes. Your counsel defines the obligation and we build the system that meets 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.
AI development elsewhere
Other metros we publish this for. The full list is here.
New York, NY
New York, Brooklyn, Queens
Boston, MA
Boston, Cambridge, Somerville
Atlanta, GA
Atlanta, Alpharetta, Marietta
Miami, FL
Miami, Fort Lauderdale, Coral Gables
Charlotte, NC
Charlotte, Concord, Gastonia
Philadelphia, PA
Philadelphia, King of Prussia, Wilmington
Detroit, MI
Detroit, Ann Arbor, Dearborn
Tampa, FL
Tampa, St. Petersburg, Clearwater
Chicago, IL
Chicago, Naperville, Evanston