Industries
Domain knowledge you do not have to explain from scratch.
Financial Services, Media and Entertainment, Manufacturing, Automotive, Retail, Healthcare & Life Sciences. If your roadmap needs engineers who already know one of these sectors, each page shows the systems we built, and the engineer you'd talk to is the one who writes the code.
Financial Services
When your lending roadmap has more work on it than your engineers can carry, ours join your team to build the origination, refinance, servicing and repossession systems, so a decision can still be defended to an examiner long after it was made.
7 case studiesStreaming, creators, fan intelligenceMedia and Entertainment
When live game delivery and audience analytics are both on your roadmap and your team can only staff one, our senior engineers join you and build them as one system, so you can tell a rights holder who actually watched.
1 case studyAnalytics, dashboards, ERP, qualityManufacturing
When the plant and finance bring different numbers to Monday's meeting and nobody on your roadmap is free to fix it, our senior engineers join your team and wire the ERP, the scale house, the line historian and the lab into dashboards both sides trust.
6 case studiesDealers, auto finance, recoveryAutomotive
Applications wait in a queue while someone re-keys the deal from the dealer's system into the lender's, and a funding delay loses the deal. Our engineers join your team and build the software that takes those steps out, with a Databricks platform that keeps dealer, lender and recovery data in one place.
8 case studiesCommerce, warehouse, fulfilmentRetail
When an order still needs someone to re-key it on its way to a doorstep and your team has no one free to fix it, our senior engineers work in your workspace to rebuild the commerce platform, the warehouse system and the ERP links until those steps go away.
2 case studiesRecord unification at scaleHealthcare & Life Sciences
We'd design PHI safeguards and clinician review into an agent before it's built, then test and deploy it with them in place: a unique identity for every user and agent, every read of patient data recorded, and a clinician approving anything that touches care.
1 case studyWhat changes the engineering in each sector
In lending the constraint is the examiner who turns up nine months later and asks how a decision was reached. That pushes the work towards durable workflows for steps that must not half-complete, and lineage good enough to replay the decision. SWBC, Auto Approve and the repossession close-out are the published work, and AutoFabric checks TILA, ECOA and FCRA rules on every agent action instead of sampling them each quarter.
In manufacturing it's six systems that each hold part of the answer. The ERP knows what was ordered, the scale house knows what came through the gate, the historian knows how hard the line ran, and none of them agree on a supplier's name.
The plant leadership study joins Business Central with all of them on Databricks, with one definition per metric in the gold layer, so "processed" means the same thing on the ramp-up chart as in the mass balance.
Retail is judged on throughput. Every manual step between an order and a doorstep costs somebody an afternoon, so the ERP integration is the first design constraint. Funko is a warehouse system built to cut operating expense, and AmTab wired a store into Business Central so orders stopped being re-keyed.
In media the problem is that rights holders get handed almost nothing about who watched. Delivery and analytics have to be built as one system so viewing lands somewhere a query can reach while the season is live, which is how BZZR carries Texas Rangers games beside creator video and podcasts.
Our health work is data unification at scale. More than 400 million athlete records for Athlinks, across sources that never agreed on who a person was, on a pipeline that resumes when a step dies instead of starting again. The governance that a clinical estate needs on top is at data and AI governance.
The first conversation, whatever the sector
The questions repeat more than the industries do. Most of what we ask in a first call is the same in a credit union and a plant, and the answers decide whether the work starts with an assessment, a build or a single integration.
What we'll ask, so you can answer it first
- Which process, if it half-completed tonight, would cost you most by Friday
- Who has to be able to explain a decision afterwards, whether that's an examiner, an auditor or a customer
- Where the system of record is, and which other systems are allowed to write to it
- Which numbers two teams currently report differently
- What has already been tried, and where it stopped
- Whether the data is on Databricks, on its way there, or somewhere else for now
Not on this list?
The problems repeat more than the sectors do. A queue someone is clearing by hand, a system of record nobody trusts, a pipeline that fails halfway and starts again from the beginning. Bring us yours.