AI for Corporate Finance & Private Equity
For CFOs, Finance Directors, and Portfolio Operations leads at PE-backed companies, mid-market corporates, and family offices under constant pressure to cut overhead and grow EBITDA. The reporting and reconciliation work usually isn't the value-add, it's the tax on getting to it.
Every portfolio company reports differently, and someone has to reconcile it
Management packs, board reporting, and deal diligence all involve the same underlying task: reading financial documents in inconsistent formats and turning them into a structured, comparable view. That work scales linearly with headcount unless something changes it.
We build the extraction and reporting layer that does the structuring automatically, so your finance team spends time on the analysis, not the assembly.
From scattered financial documents to a comparable view
Build-and-transfer, integrated with your finance stack
Discovery
We map where financial data currently lives across your portfolio or finance function, and where the manual roll-up or review work actually sits.
Build
We build the extraction, reporting, or forecasting pipeline on your infrastructure, integrated with the finance stack you already use.
Shadow-run
Your finance team runs the system alongside the current process before we step back, comparing outputs directly.
Handover
Full documentation, source code, and training, so your team owns and can extend the system independently.
Tell us which reporting cycle costs you the most time
One conversation is enough to scope it. Fixed-fee. Integrated with the finance stack you already use.
info@kelriva.aiAI for Corporate Finance & Private Equity: what buyers actually ask
Can this work across multiple portfolio companies with different systems?
Yes, that is the usual starting condition, not an edge case. We design the ingestion layer to handle inconsistent formats and systems across portfolio companies, normalising into one comparable structure rather than requiring every company to standardise first.
How do you handle data security across a portfolio?
Systems are built on infrastructure you control, with access and data residency scoped explicitly during discovery. We do not require pooling sensitive financial data on a shared third-party platform.
Can this integrate with our existing finance and BI tools?
Yes. We integrate with ERP and finance platforms, data warehouses, and BI tools via APIs and direct connections, building around your existing stack rather than replacing it.
What does a corporate finance AI engagement cost?
The AI Readiness Assessment (£4,500, 9 to 14 days) is a common starting point to audit data maturity across a portfolio or finance function. A full reporting or extraction pipeline build is scoped and fixed-fee after that, typically in the same range as our IDP Proof of Concept (£8,500, 3 to 5 weeks) or larger depending on scope.
Do you have a live client reference in this sector?
Not a named one in corporate finance or PE specifically, and we would rather say that directly than imply otherwise. Our live production reference is in corporate coaching (bettercoach), and our enterprise SaaS client used the same document-processing pattern a financial-document pipeline would require.