Real workflows. Measurable results.
Every engagement starts with a Data Assessment. Here's what happened next.
How a retail scale-up reduced pipeline delivery time by 60%
60%
Faster pipeline delivery
40+
Backlog items cleared in month one
0
New hires required
The challenge
A fast-growing retail company had a backlog of 40+ pipeline requests sitting idle. Their two data engineers were spending most of their time on incident response and maintenance — not building. Every new request added to the queue, not the product.
What we did
The first Context Engine was generated from 18 months of Azure DevOps history and refined around their Medallion architecture standards. Agents took over pipeline builds, documentation updates, and error debugging. Senior data engineers focused on architecture decisions and complex transformations.
“Our engineers finally have time to build things that actually move the business forward. The agents handle the rest.”
— Head of Data Engineering, Retail Scale-up
How a financial services firm onboarded 3 new data projects in under 2 weeks
12 days
Three projects delivered
100%
Within their Azure tenant
3×
Parallel capacity without 3× headcount
The challenge
Three parallel compliance data projects with a hard regulatory deadline. The internal team had capacity for one. Hiring was off the table — not enough time, and security requirements made external access complicated.
What we did
Everything ran inside their Azure tenant from day one — no data left the environment. Your Context Engine loaded their compliance standards, naming conventions, and audit trail requirements automatically. Three project tracks ran in parallel, each with full context of the firm's standards.
“We couldn't have hired fast enough. And honestly, the output quality matched what our best engineers would have delivered.”
— Data Platform Lead, Financial Services
How a logistics leader built a self-service analytics platform on Microsoft Fabric
30+
Ad hoc requests eliminated per month
12
Teams now self-serve
3 months
Fabric lakehouse live
The challenge
Twelve business teams, each with their own spreadsheets and manual reports. The data team was fielding 30+ ad hoc requests a month. No single source of truth, no way to scale, and a Fabric migration already stalled for six months.
What we did
The Data Assessment mapped every reporting workflow, classified which could be automated, and produced a phased Fabric migration roadmap. Within three months, a shared Fabric lakehouse with Power BI semantic models gave all twelve teams self-service access — with no data team involvement for standard requests.
“The Data Assessment found things we didn't even know we were spending time on. The roadmap it produced was the clearest output we'd ever seen from an external partner.”
— Analytics Lead, Logistics
How an enterprise team eliminated knowledge loss during a major data team transition
4 years
Of institutional knowledge captured
0
Knowledge gaps reported after transition
2 weeks
Full extraction and handover
The challenge
Three senior data engineers were leaving within a 90-day window. Between them, they held the architecture decisions, data model rationale, and pipeline reasoning for a four-year-old estate. Standard documentation would never capture it all in time.
What we did
A Context Engine was generated from four years of Azure Repos commits, pull request comments, and DevOps work items. Ontology, business context, data lineage, and code patterns were structured before anyone handed in their notice. The team that followed had full context from day one.
“We thought we were going to lose years of context. Instead, the new team had more structured knowledge of our environment than we did.”
— CTO, Enterprise data platform
How a fast-growing e-commerce brand scaled data capacity without a single new hire
5
Workflows automated in month one
2×
Effective team capacity
€0
Additional headcount cost
The challenge
Revenue doubled in twelve months. Data requests tripled. The two-person data team couldn't keep up — and seasonal spikes made the gap even worse. The CFO had blocked new headcount until next financial year.
What we did
Five workflows were automated after the Data Assessment and Implementation: order analytics, inventory data quality checks, returns pipeline, weekly BI refresh, and supplier data reconciliation. The team's capacity for new projects doubled without a single new hire.
“We onboarded yourdatateam.ai on a Monday. By Friday, two workflows were already running without us. That had never happened with any vendor we'd worked with before.”
— Head of Operations, E-commerce
See what we'd automate in your environment.
The Data Assessment maps your actual data workflows, classifies every task, and hands you a prioritised automation roadmap — built from your own numbers, in two weeks.
Book the Data Assessment€4.500 · Fixed price · Two weeks