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AI consulting and development · Philadelphia, PA

AI consulting and development for Philadelphia companies

An AI pilot that reads patient records or claims can't go to production until it shows the record behind every answer and stops for a person when it should. Our senior engineers build that with your team: retrieval that cites its source, agents that pause for the clinician or adjuster, and evals on every change. Philadelphia's teaching hospitals and the insurers of Center City set that bar, and drugmakers across the river meet it too.

Founded

2017, and still independent

Bench

115+ engineers, 80 Databricks-certified

Experience

Fifteen years average, per engineer

Serving

Philadelphia, King of Prussia, Wilmington, Camden

Health systems and universities first, pharmaceutical manufacturing across the New Jersey and Delaware border, and an insurance sector older than either. If you're in one of them, a wrong answer from a model is a patient or a claim, and the system has to be built knowing that.

DatabricksTemporalAzure

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 Philadelphia

Philadelphia's AI consulting work starts with patient and claim data, in the hospitals of University City and the insurers on Market Street. Before any model reads a record we agree which data it may see, where a clinician or an adjuster must decide, and how a wrong answer gets caught, then build only the use cases that hold up under that plan.

Minimum necessary belongs in the platform

Philadelphia runs on health care. Penn Medicine, Jefferson and Children's Hospital of Philadelphia are among the region's largest employers, and Independence Blue Cross pays claims from Market Street. HIPAA's minimum-necessary standard covers all of them, so a report, a service account or an agent that reads more patient data than its task needs is a use the rule doesn't permit, whatever the intent behind it.

Minimum necessary usually lives in a policy and gets enforced in application code, one service at a time, which holds until the third tool arrives. We put the grant in the data platform instead, resolved at read time, so a Power BI report, a notebook and an agent all get the analyst's view and nothing wider. A shared service account with broad read access is the shortcut we refuse.

Work starts with an access inventory. Every identity that reads protected data, human or not, gets listed beside what its job needs, and the gaps become row filters and column masks in Unity Catalog before a single pipeline moves, and any agent's evals include a test that it can't see a record its user couldn't.

Clients we have done this for

Patient indexes and claims files are built from records stitched together across sources, and Athlinks needed a pipeline to do that for more than 400 million athlete records. The study shows the multi-tiered serverless architecture built on Temporal for it, with granular control, automated retries and real-time visibility across the whole run.

Health & Wellness

AthlinksAthlinks

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

  • Verizon
  • Location Services
  • SRS Distribution

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.

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.

A sentence or two is plenty, such as what it should do and what stands in the way today.

Goes straight to a senior engineer. By sending this you agree we can contact you about your enquiry, and occasionally about our work. Tell us to stop at any time and we will.

Around Philadelphia

Philadelphia's AI hack nights and Penn's labs

AI Philly runs a hack night most months on a Tuesday at Blockspace on South Broad Street, for people building with agents. Philly AI Connect meets every two or three months at the Pennovation Center beside the Penn campus and ran a full-day summit during Philly Tech Week 2026, and Tech Week returns 3 to 8 May 2027. Penn Engineering's Raj and Neera Singh Program teaches AI to undergraduates and, online, master's students.

Much of that sits a short walk from the Hospital of the University of Pennsylvania, which is a fair reminder of who reviews AI in this city. In a hospital or a claims department, a clinician or an adjuster decides where the model has to stop for a person, and that decision belongs in the design before the first prompt is written. Our agents ship with that pause point and its eval agreed up front.

Map of the Philadelphia-Camden-Wilmington metro area11 counties: Bucks County, PA; Chester County, PA; Delaware County, PA; Montgomery County, PA; Philadelphia County, PA; New Castle County, DE; Cecil County, MD; Burlington County, NJ; Camden County, NJ; Gloucester County, NJ; Salem County, NJ. The lighter shape is Philadelphia city, and the red dot marks downtown Philadelphia.

The Philadelphia-Camden-Wilmington metro area. Pennsylvania: Bucks, Chester, Delaware, Montgomery and Philadelphia counties. Delaware: New Castle County. Maryland: Cecil County. New Jersey: Burlington, Camden, Gloucester and Salem counties.

Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.

  • Meetup · Monthly, usually a Tuesday evening, plus occasional talks

    AI Philly

    Bring the engineer who'll own your first agent, since the hack nights at Blockspace on South Broad are spent building with agent tools rather than watching slides.

    Volunteer organisers. Blockspace Philly, 215 S Broad St, Center City.

  • Meetup · Roughly monthly, weekday evenings

    Data Science Philadelphia (DataPhilly)

    At about 6,100 members it's the region's biggest data science room, and its talks on putting AI into production are the ones a hospital team should prioritise.

    Volunteer organisers. Rotates between Penn's Huntsman Hall, Slalom at Two Logan Square and Villanova.

  • Meetup · Every two to three months

    Philly AI Connect

    Researchers and founders share the room at Pennovation, so you hear where academic AI work is heading before anyone is selling it to you.

    Volunteer organisers. Pennovation Center, 3401 Grays Ferry Ave, beside the Penn campus.

  • University · Ongoing degree programmes

    Raj and Neera Singh Program in Artificial Intelligence (B.S.E. in AI and M.S.E. in AI Online), University of Pennsylvania

    Penn teaches its AI degrees with ethics inside the technical coursework, which is close to the vocabulary a hospital's review board will expect from any agent project.

    Penn Engineering, University of Pennsylvania. University of Pennsylvania, University City; the M.S.E. is online.

  • Conference · 3 to 8 May 2027

    Philly Tech Week

    If you can clear only one week, make it Tech Week in May, when local organisers fill the calendar with AI, developer and startup sessions.

    1Philadelphia (1PHL). Venues across Philadelphia.

More in Philadelphia (4)
  • PhillyBricks (Philadelphia Databricks User Group)

    A Databricks user group for data engineers, architects, analysts and AI practitioners across Greater Philadelphia. Evenings pair a technical talk, often from Databricks engineers, with networking.

    Every few months, weekday evenings. Indy Hall, Northern Liberties, or iThrive Coworking, Paoli.

  • Philly Data & AI

    A data and AI meetup of about 3,000 members for data scientists, data engineers, students and newcomers. At the moment it meets as a monthly evening happy hour.

    Monthly, a Tuesday evening. Con Murphy's Irish Pub, 1700 Benjamin Franklin Pkwy, Center City.

  • MSE in Data Science, University of Pennsylvania

    A Master of Science in Engineering covering machine learning, big data analytics and statistics, with a specialisation in an applied field. Most students finish in eighteen months to two years.

    Ongoing degree programme. University of Pennsylvania, University City.

  • Master of Science in Data Science, Drexel University

    An interdisciplinary master's covering machine learning, NLP, large language models and data governance, ending in a capstone. Students study on campus or online, with an optional graduate co-op.

    Ongoing degree programme, fall and winter starts. Drexel University, University City, and online.

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 Philadelphia: common questions

Do you work with Philadelphia companies?

Yes, and 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 Philadelphia?

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 enforce minimum necessary access under HIPAA?

An agent or a service reads through the same grants a person would, resolved at read time. There is no service account with broad access sitting behind the application, because that is the shape that turns an inefficiency into a breach.

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.