Welcome to Datavrn

Every reporting cycle, in finance teams across the world, someone opens an Excel file and starts the same work they did last cycle.

Pull the trial balance. Map accounts to the right buckets. Allocate shared costs across departments. Carve out leadership compensation from the bulk payroll entry. Spread the annual depreciation across twelve months. Consolidate the operating entity with the holdco. Translate the subsidiary’s books into the parent currency. Match inter-company transactions. Eliminate the duplicates.

By the time the management report is ready for whoever needs it — board, CFO, investor, parent company — eight to fifteen hours have passed. Per entity. Per cycle.

Multiply by every entity, every cycle. That’s the bottleneck.

We’re building Datavrn to remove it.

Who this is for

Datavrn is for finance teams that produce management reporting on a regular cadence. Specifically:

In-house FP&A teams at growing companies. If your team produces monthly or quarterly reporting for management, a board, or investors, runs allocations across cost centres or business units, and spends the first two weeks of every cycle assembling instead of analysing, this is built for you.

Finance leaders and CFOs. If you’re tired of your team’s quality of analysis being limited by their assembly time, and you want a methodology layer that doesn’t break as the business grows, this is built for you.

Outsourced and advisory finance practices. If your team handles management reporting for multiple clients, has methodology that lives in senior managers’ heads or in Excel files, and wants to handle more client work without adding headcount, this is built for you.

If your work is statutory audit, return filing, or bookkeeping, Datavrn is not the right fit. The product assumes active management reporting work — a methodology layer producing analytical reports for decision-makers.

What’s different about it

A few things we’re deliberately doing:

Methodology as a first-class concept. Cost centres, allocation rules, period spreading, carve-outs, profit centres, budgets, variance explanations — these aren’t features bolted onto a reporting tool. They’re the spine. The tool encodes how a team thinks about management reporting, then applies that thinking automatically every cycle.

Multi-entity consolidation, properly. Most reporting tools handle one entity. Datavrn handles the operating company plus holdco setup, the parent with international subsidiaries, the group of three companies under common ownership. Inter-company eliminations, minority interest, currency translation — done correctly, with full audit trail.

Platform-agnostic. The methodology layer doesn’t care where the data comes from. It will work with accounting systems, ERP exports, and spreadsheet uploads. This matters whether you’re consolidating subsidiaries on different systems or managing clients across different accounting platforms.

Built with deep finance domain knowledge. Not by software people guessing at what finance professionals need. The methodology, the report structures, the way numbers tie out — all calibrated by people who have produced these reports by hand for years.

What we’ll be writing about

This is where the writing about the work goes.

We’ll publish posts covering things like:

• Cost centre allocation methodology — what works, what breaks, what to avoid
• Multi-entity consolidation patterns and the common failure modes
• Specific carve-out and period-spreading scenarios from real practice
• How FP&A teams can professionalize their reporting layer
• How outsourced finance practices can systematize client reporting
• Notes from the build itself when worth sharing

This blog is for finance professionals. We won’t write generic SaaS marketing content. We won’t write about AI hype. We’ll write about the actual work.

Where we are

Datavrn is in active development. We’re working with a small group of design partner organizations ahead of general release. If your team produces management reporting and you’d like to be considered, join the waitlist.

We’ll be in touch as the product gets closer to launch.

— The Datavrn team