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INDUSTRY · SOFTWARE COMPANIES

Turn your application's data into features customers pay for.

We move analytics off your production database onto Microsoft Fabric. Then we build reporting into your product, designed so each customer sees only their own data.

↳ Work our team has delivered: 10× analytics query throughput for a shipping software platform.Some of this work was delivered by Reenva's founder and team before Reenva was formed.

/01 · The problem

You don't have a data shortage. You have an access problem.

Your application holds data your customers would pay to see: history, trends and benchmarks. But it was built to run the product, not to answer questions. So reporting runs off the production database and slows down as you grow.

Serving each customer only their own data is harder than it looks. Workarounds that suit a few customers often strain as you add more.

The fix has two parts: move analytics off the production database, then turn the result into a product. We build on Microsoft Fabric.

/02 · How we build it

From raw application data to analytics customers pay for, in three steps.

Skipping a step makes reporting slow and risky later, so we do them in order.

  1. /01DATA

    Move analytics off production

    We copy changes from your production database into Microsoft Fabric as they happen. Reports then run against Fabric, not your application's database.

    What we automate here

    • Changes copied from production into Fabric, so analytics queries leave your live database
    • Data quality checks on each table, so problems surface before they reach a report
  2. /02CUSTOMER DATA

    Keep each customer's data apart

    We design how customer data is separated, to suit your customer count, contracts and queries. Then we define each metric once, so every report agrees.

    What we automate here

    • A separation model chosen for your customer count and contracts
    • One definition per metric, versioned with your product releases
  3. /03PRODUCT

    Put analytics in your product

    Power BI Embedded reports, styled to match your product. Plain-English questions on Azure OpenAI can follow.

    What we automate here

    • Access tokens issued for each customer from your own server
    • Usage tracking that shows which reports customers use, to help you price the tier

/04 · How a project runs

We check your data before we build on it.

No reporting or AI ships until the data underneath is moved, separated and checked. The review tells you how long that takes.

If it misses the agreed outcome, we fix it. You own 100% of the IP in what we build. We reply within one business day.

Our engineers work as part of your team.

We build on Microsoft Fabric and Azure. If your analytics must stay on another cloud platform, we're probably not the right fit.

  1. /01

    A 30-minute call

    Tell us the problem. We say plainly whether we can help.

  2. /02

    A two-week fixed-fee review

    We check your data and the way the work flows. You get a clear go or no-go.

  3. /03

    A fixed-price build

    We build in your own Microsoft environment, at a price agreed before we start.

Systems we can connect

  • WarehouseMicrosoft Fabric
  • Transformationdbt · Fabric notebooks
  • Embedded analyticsPower BI Embedded
  • Source systemsPostgreSQL · SQL Server
  • AIAzure OpenAI
  • InfrastructureAzure · GitHub Actions

/05 · Work our team has delivered

SOFTWARE · SHIPPING

A shipping software platform, with customers worldwide.

10×

analytics query throughput, after moving 2,000+ source tables to Microsoft Fabric

stack
Microsoft Fabric · OneLake · Power BI Embedded
timeline
6 months from kickoff to data products live with customers
Read the shipping software case study

Some of this work was delivered by Reenva's founder and team before Reenva was formed.

/06 · Common problems

Customers want their data. Your production database can't serve it.

If one of these sounds familiar, we can help.

  • In-product reports run off the production database and slow down as customer numbers grow.

  • Enterprise buyers ask for their data in their own warehouse, and there's no quick way to deliver it.

  • Customers want peer benchmarks and the data exists, but serving it risks exposing one customer’s data to another.

  • An analytics tier was priced at launch, then the reporting layer couldn't keep customers' data apart as numbers grew.

/07 · Questions buyers ask

What software companies ask first.

/08 · Your next step

Your application data is already there. Your customers just can't see it yet.

Book a 30-minute call

After the call, a two-week fixed-fee review gives you an honest go or no-go before any project starts.