AI agents on Databricks, governed from the first design.
Azure
Google CloudOperational risk, compliance and controls designed in, then tested and deployed with them.
Winner in Databricks' global AI app contest, the Genie-Powered App Challenge, 2026Why data teams call us
The team you call when it stalls.
The migration has been nearly done for a year.
Half the jobs moved and the rest still run on Synapse, Teradata or Snowflake, so you're paying for both. We count what actually runs, then cut over in waves you can reverse.
Finance and operations bring different numbers to the same meeting.
Usually nobody wrote down the grain. We define each measure once, in governed tables, so every dashboard reads the same number.
The AI pilot worked in the demo and stopped there.
We put the model or agent on the permissions, logging and monitoring production asks for, with a person approving where it matters.
The pipeline backlog grows faster than your team can clear it.
Our engineers join your team in your repositories and leave pipelines your own people can run and explain.
Client results
Real clients. Real numbers.
- Athlinks · Temporal · AWS
Sources that never agreed on who an athlete was, and a matching run that couldn't restart if it died halfway. 400M+ Athlete records unified.
Read the case study - Auto Approve · Azure · React
Loan agents copying every refinance request by hand between the CRM, lender sites and Excel. 2× Monthly loans processed, with no additional agents hired.
Read the case study - Funko · Dynamics 365 Business Central · AWS
Distribution moved into one Arizona warehouse, and the system running it had to keep up. 2× Operational efficiency.
Read the case study
Production software for companies that needed more than a dashboard.
Why us
Senior engineers, no junior bench.
80
Databricks-certified engineers
An award-winning Databricks engineering team, certified on the platform you run.
15 yrs
Average experience per engineer
They've worked in unfamiliar enterprise codebases many times, so the ramp on yours takes days.
115+
Engineers across four offices
Gilbert in the Phoenix metro, Amsterdam, Dnipro and Hyderabad, with one way of working across all four.
Winner
Databricks Community Genie-Powered App Challenge, 2026
Creativity & Originality track, second place. And we're a Databricks partner that runs its own company on the same stack.
The winning appFill the seat.
Own the problem.
The engineers who scope the work build the system and remain on it at go-live. The people in the first call are still there when production traffic arrives.
Databricks consulting
Databricks, done right the first time.
Data engineering and ETL
Lakeflow pipelines and medallion tables that land on time, with data quality checks on every layer and a cost your team can see.
Migration to Databricks
Off Snowflake, Synapse, Teradata, Hadoop and SQL Server, scoped before you commit to a date and cut over in waves you can reverse.
Governance with Unity Catalog
Catalogs, permissions and lineage designed so the grants actually hold and the auditor's questions have answers.
MLOps
Models that leave the notebook, with features defined once for training and serving, every run tracked in MLflow and a monitored endpoint on Model Serving.
AI agents
Agents built around your risk and compliance rules, working under their own identity and your Unity Catalog permissions, with a person approving where it matters.
Lakebase applications
Postgres inside the lakehouse, and the application your people use on top of it.
Databricks is the platform we have gone deep on, and Temporal sits underneath the operations that must not fail. Where a system has to reach past the workspace we build on Azure, AWS, Google Cloud and Cloudflare too.
27
source platforms our migration playbooks cover, from Snowflake and Synapse to Teradata and SAP. Before you commit to a date, two weeks at a fixed fee inventory the estate, find the jobs that matter and the tables nobody has queried in a year, and end in a wave plan.
Before the model
The grants decide what your agent can say.
An agent that inherits a user's Unity Catalog grants can't hand back what that user was never allowed to read. Tell it the same thing in a prompt and you're trusting the model's judgement, which is a harder promise to make to an auditor. So we design the catalog and the grants before anyone builds on top of them.
What TechFabric does, in two minutes
Transcript
Show the transcript
We're definitely at an inflection point like we haven't seen, frankly, since, like, the mid-'90s. Things are about to change. And so, we are, every company that we're dealing with, all of our customers, we're already starting to have these conversations. Is there a different way that we should be thinking about how your customer is interacting with your service?
The beautiful thing about TechFabric is we're not working with one client. We're working with, you know, like 25, 30 clients. Our job is to always be on the cutting edge, keep track of what's happening in the industry, and then map those advancements in technology to business problems.
One of the things TechFabric has kind of earned a reputation for doing is picking up where other people failed. Our job as product people is to make something that may seem impossible possible.
If you've got a challenging project that you want to talk about, let's talk. We are really passionate about using technology to solve problems, and that means always being ahead of the curve, like always learning newer technologies, always learning newer ways of solving problems.
Every business is different. Something which might work for me might not work for you.
We look for engineers who have that something extra, who will, you know, they're up at three o'clock in the morning still solving that problem. They're really trying to look deeper into reading between the lines and give the best possible product. We get, like, emotionally, mentally invested into that project.
We want that project to succeed and we want the client to be happy. We really deep dive into the complexities of their business and the intricacies and the unique problems that they have. They're puzzle solvers. They love to, okay, let me take that on. Let me rip it apart. Let me understand it.
Let me look at it from 27 different angles. It's not a sales thing, you know. We're just trying to help you solve a problem. And if you like how we approach that, you're going to enjoy working with us. We become an extension of their internal teams. And that, we believe, is what makes a good tech partner.
Transcribed from the video's audio. Stutters, repeated words and a few filler words are left out.
Our engineers don't start from an empty repository.
We bring seven accelerators of our own to the work, for moving an estate, building and testing agents, and keeping people in control of them. They're free and Apache-2.0 licensed, they run inside your Databricks workspace under your Unity Catalog, and nothing stops working the month we leave.
Beyond Databricks
We also build software, and implement Dynamics 365.
Software on Lakebase and other clouds
Custom web and mobile applications were the trade we started in, years before our Databricks bench. We still build them, on Lakebase or on Azure, AWS and Google Cloud. Custom software development.
Dynamics 365 and Business Central
We're a Microsoft Solutions Partner and implement Dynamics 365 Business Central, and AmTab's modernisation ran on Dynamics 365 and Power Automate. Start with Dynamics 365 consulting, Power BI reporting or the Business Central reporting assessment.
FAQ
How we build governed AI agents
How do you build governed AI agents on Databricks?
We design the governance in before the agent is built. Operational risk, compliance and control requirements are written as policy at design time, the agent works under its own identity and Unity Catalog permissions, and every action it proposes is checked against that policy before anything changes.
Each decision is recorded with the policy version that made it, and the same checks run in testing and in production. Our AI agent services cover the build, and the Field Guide's chapter on governed actions shows the pattern.
Can governance be added to an AI agent after it's built?
It can, at a higher cost. By then a dozen call sites hold credentials and no record of what the agent proposed exists for a policy to check, so the boundary between the agent and the systems it changes has to be retrofitted. At the first design review that boundary is a single interface, so that's where we draw it.
How do product, engineering, operations and risk teams work together on an agent?
Around one policy that all four can read. Risk and compliance write their requirements as policy that sits beside the agent's code and changes through the same review.
Product decides which actions the agent may propose, engineering builds the proposal and the check, and operations owns the queue where a person approves what policy sends to them. Any decision can then be traced to the rule and the person behind it.
Where have you built governed agents?
In AutoFabric, our own product for auto lenders. Its agents run origination and refinance steps such as credit pulls, stipulations and payoff quotes on Unity Catalog and Databricks Apps, and every action is checked against policy, with TILA, ECOA and FCRA built in, and recorded for the examiner.
From our engineers
All articles- Oct 27, 2026 · Raja Vemuri
Unity Catalog model names return 404 on /serving-endpoints
A system.ai model name on a Databricks workspace's /serving-endpoints path returns 404 with Unity Gateway enforcement off. Why we route by name, not by URL.
Read the article - Oct 27, 2026 · Preetham Reddy
Search that keeps up with a live game and an open loan
We indexed a wine catalog and refinance queues at iLending and Auto Approve. Search can now read a streaming table or a materialized view.
Read the article - Oct 27, 2026 · Ihor Seleznov
How we test that AUTO CDC keeps the right customer record
A Databricks CDC flow can finish green and still keep a customer's old city or bring a deleted customer back. How we test ordering and deletes before release.
Read the article
Put that project back on the roadmap.
Bring the project, the deadline and the system it has to fit. A senior engineer will work through the first decisions with you.