AI consulting and development · Seattle, WA
AI consulting and development for Seattle companies
An agent that demos well won't reach production until someone can show how it's governed, how it's scored and what it costs to run all day. Our senior engineers build agents that hold state across a multi-day order, retrieval that respects each user's grants, and evals that run before and after every change. In Seattle that's an online retailer in South Lake Union, an aerospace supplier near Paine Field, or a Bellevue software company.
Founded
2017, and still independent
Bench
115+ engineers, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
Seattle, Bellevue, Redmond, Tacoma
Cloud software on the Eastside, commerce at global scale and the aircraft Boeing assembles in Everett and Renton, the very abstract and the very physical in one metro. Whichever side you work on, governance, evaluation and what a system costs to keep running tend to come up in the first meeting rather than the last.
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 Seattle
For a Seattle commerce team in South Lake Union or a logistics operator in the Kent Valley with its own platform engineers, AI consulting is mostly about what happens after the first agent works. We cover governance, evaluation and the cost of running agents continuously, and finish with an architecture and a budget that team can own.
In Washington, a shopping basket can be health data
Seattle sits under Washington's My Health My Data Act, which reaches well past hospitals to the online retailers of South Lake Union and the warehouses of the Kent Valley. Infer a health condition from a shopping basket and you hold consumer health data, which needs consent to collect or share and must be deleted on request, backups included. Consumers can sue under the state's Consumer Protection Act.
Most commerce estates can't prove a deletion, because nobody knows how many copies of a customer exist. There's the order table in the warehouse, a marketing extract, a feature store for recommendations and three analysts' notebooks. We won't call a deletion done until lineage can list every table that held that customer, and the run that removed them has left a record of its own.
The first two weeks map copies. We switch on Unity Catalog lineage across the estate, tag the columns that could reveal health information, and run one real deletion request end to end, timing each step through to the Delta VACUUM that removes the old files. What breaks becomes the backlog, and the migration is planned around it.
Clients we have done this for
Online orders end in a warehouse, where software has to keep pace with physical work. At Funko, the warehouse management system was built to cut operating expense, reduce reliance on manual work and double throughput efficiency, and operational efficiency doubled.
Warehouse management
Funko
Funko consolidated its distribution into one Arizona warehouse and needed the system running it to keep up. Our engineers went on-site and sat with the warehouse and operations teams, extended the module Funko already had instead of starting over, and the warehouse doubled its operational efficiency.
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 Seattle
Seattle's AI evenings, track by track
AI Tinkerers Seattle runs several tracks at once, with demo nights, AI developer tools, go-to-market AI and a Women in AI builders group, so there's an evening most weeks. Global AI Seattle alternates between Seattle and Bellevue roughly every two months, free and in person, and GDG Seattle runs labs on Google's AI tools through the year ahead of DevFest Seattle at the SURF Incubator on Third Avenue.
The University of Washington adds a slower rhythm. Its MS in Data Science ends in a two-quarter capstone for an outside organisation, and the eScience Institute works with research groups across campus on applying AI. For a company with a narrow, well-posed question and data it's able to share, that's a route to a first answer, provided you can wait two quarters for it.
The Seattle-Tacoma-Bellevue metro area. Washington: King, Pierce and Snohomish counties.
Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.
Meetup · Several evenings a month
AI Tinkerers Seattle
Separate tracks for dev tools, go-to-market AI and Women in AI builders mean you can pick the evening that matches the system you're building.
AI Tinkerers, Seattle chapter. Venues vary across Seattle.
User group · Roughly every two months, weekdays
Global AI Seattle
Free and in person, alternating between downtown and Bellevue, these meetups draw developers building with AI from across the metro rather than one vendor's users.
Volunteer organisers, Global AI Community. Rotates between Seattle and Bellevue.
Meetup · Several evenings a year
Seattle Spark+AI Meetup
AI that runs on customer data starts in Spark pipelines, and this Bellevue group is where you'll hear how other companies keep theirs reliable.
Volunteer organisers. Rotates between member companies' offices in Bellevue.
University · Ongoing
UW eScience Institute
University of Washington research groups apply data science and AI here, a source of methods worth borrowing when your evaluation needs more rigour.
University of Washington. University of Washington, Seattle.
University · Ongoing part-time degree programme, evenings
Professional Master's Program (PMP), Paul G. Allen School of Computer Science & Engineering
One evening a week at the Allen Center, working engineers study computer science while keeping their jobs, so your own staff can upskill without leaving.
University of Washington Paul G. Allen School. Paul G. Allen Center, 185 E Stevens Way NE, University of Washington.
More in Seattle (2)
- GDG Seattle (DevFest Seattle 2026)
Seattle's Google Developer Group runs labs on Google AI and Cloud tools through the year and hosts DevFest Seattle, a one-day conference with talks, workshops and demos.
7 November 2026. SURF Incubator, 999 3rd Ave, Downtown Seattle.
- Master of Science in Data Science, University of Washington
A professional master's in data science with eight core courses and a two-quarter capstone for an outside organisation. Classes are in the evening, full-time or part-time.
Ongoing degree programme, 18 months full-time or 30 part-time. University of Washington, Seattle, evening classes.
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 Seattle: common questions
Do you work with Seattle 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 Seattle?
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.
How do you handle deletion and retention across a commerce estate?
As a platform capability rather than a policy page. Retention rules and deletion requests act on the event log and the projections derived from it, so a deletion is a real operation with a record rather than a job somebody runs and hopes about.
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 Seattle
What else we build for Seattle companies.
Software development in Seattle
Headcount won't arrive this quarter, and the order process spread across six systems still stops halfway whenever one step times out.
Databricks consulting in Seattle
Auditors keep asking where every copy of a customer lives, and with duplicates across the warehouse nobody can prove a deletion.
AI consulting and development elsewhere
The same work, in other metros. The full list is here.
New York, NY
New York, Brooklyn, Queens
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Boston, Cambridge, Somerville
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Atlanta, Alpharetta, Marietta
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Tampa, St. Petersburg, Clearwater
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