Skip to content
TechFabric

AI development · New York, NY

AI development for New York companies

New York runs on money moving and on the reporting that has to explain it afterwards. Banking, asset management, insurance and the fintech layer built on top, alongside the advertising and media businesses that sit beside them.

Every one of those businesses has the same AI problem, which is that an automated decision affecting a customer's money has to be explainable to somebody who is allowed to ask. That is the constraint we build around rather than the one we discover afterwards.

Founded

2017, and still independent

Bench

115+ people, 80 Databricks-certified

Experience

Fifteen years average, per engineer

Serving

New York, Brooklyn, Queens, Jersey City

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, which is what makes the difference between a demo and something a regulated team is allowed to ship.

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.

Work a New York buyer would recognise

SWBC is a financial services group, and the work is the sort of governed platform build a New York buyer would recognise immediately.

Automotive / Fintech

SWBC

TechFabric rebuilt SWBC's LOSExpress platform for credit unions: the user experience, the design system, and the front-end architecture.

The examiner arrives eventually

NYDFS Part 500 and SOX both want the same thing from a system: a demonstrable answer to who changed what, when, and under whose authority. Building that as an event log the platform produces is cheaper than reconstructing it from application logs the week before an examination.

None of that is unusual for New York, 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

Where we work from

TechFabric is headquartered in Gilbert, Arizona, in the Phoenix metropolitan area, and works with companies across the United States. We do not keep an office in New York and are not going to pretend otherwise on a page you found by searching for one.

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 because that suits the work. We travel for the parts that go better in a room, which is usually discovery, workshops and the opening weeks of a build.

Headquarters

1530 E Williams Field Rd, Ste 201
Gilbert, AZ 85295

Phone

+1 (480) 681-6806

Also

Amsterdam, Dnipro, Hyderabad

FAQ

AI development in New York: common questions

Do you work with New York companies?

Yes. TechFabric is headquartered at 1530 E Williams Field Rd, Ste 201, Gilbert, AZ 85295, and works with companies across the United States. 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.

Do you have an office in New York?

No. We have one office and it is in Gilbert, Arizona. Most of this work is remote or hybrid because that is what suits it, and we travel for the parts that go better in a room, usually discovery, workshops and the opening weeks of a build.

Can you satisfy a NYDFS Part 500 review?

We build the evidence the review asks for as a property of the platform rather than as a reporting exercise. Every domain change passes one pipeline, the event that explains it is written in the same transaction, and the trail reconstructs rather than approximates. What we do not do is certify you: your auditor does that, and our job is to make the answer easy to produce.

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.