Case Study · IT Outsourcing
From Chaos to Financial Clarity
How a mid-size IT outsourcing company moved its monthly close from day 25 to day 5 - powered by AI, with zero new hires.
Client
Kitrum
Service delivered
Fractional CFO + AI Finance Automation
Industry
IT Outsourcing
01 - Client Context
A growing IT company drowning in its own data
Kitrum is an IT outsourcing company providing staff augmentation and managed delivery services across Europe and North America. The business had grown steadily over five years - but the finance function hadn't kept pace.
Monthly reporting relied on a patchwork of spreadsheets maintained by 5 full-time accountants. Revenue recognition was done manually across 40+ active contracts with different billing cycles, currencies, and delivery models. The CEO received financial summaries on day 25 of the following month - by which point decisions were being made on assumptions, not facts.
02 - The Challenge
Four problems compounding each other
Close on day 25
Reports arrived too late to act on. The next month had already started.
Unstructured financial data
All reports existed - but scattered, with no consolidated view for decisions.
Manual, error-prone processes
Invoicing and reconciliation done by hand - creating rework and audit risk.
Too many dashboards, no clarity
Multiple tools, conflicting numbers. No single source of truth for decisions.
"We knew roughly how much we were making. We had no idea why, or what was eating our margin."
03 - Our Approach
A structured intervention in three phases
Whales Finance deployed a Fractional CFO alongside an AI Finance Automation build-out. The engagement was scoped as a 6-month transformation with clear milestones. AI was central to the speed of results: by replacing manual data collection and reconciliation with intelligent pipelines, the entire close process ran 3× faster than what the same team could achieve manually.
Weeks 1-3
Finance audit & data architecture
We mapped every data source - time-tracking systems, invoicing tools, bank feeds, payroll - and identified the root causes of the slow close. The core issue: 11 manual handoffs between systems, each introducing delays and errors.
Weeks 4-8
Automated reporting infrastructure
We built automated pipelines for P&L, Cash Flow, and project-level margin - replacing all 11 manual handoffs. Real-time dashboards were connected directly to operational data. Close cycle work was reduced to exception review only.
Months 3-6
Strategic CFO layer
With clean data in place, we introduced unit economics tracking by client and delivery model, a 13-week rolling cash forecast, and a contract profitability framework that flagged margin-negative accounts before renewal.
Month 1
Audit & architecture complete
Month 2
Automated infrastructure
Month 3
First 5-day close
Month 6
Full CFO layer operational
04 - Results
Numbers that speak for themselves
Monthly close moved from day 25 to day 5 - the earliest close in the company's history, powered by AI automation
Gross margin improvement after eliminating margin-negative client contracts identified by the new unit economics model
AI made the entire process 2× faster - intelligent pipelines replaced manual reconciliation across all 11 data handoffs
Additional headcount added. All gains delivered through process re-design and AI automation - no new finance hires required
Anna joined at a time when our finance function needed a full reset, not incremental fixes. As Fractional CFO, she rebuilt core processes, redesigned KPI dashboards, and improved cross-functional alignment and team performance. The impact was clear: operational margin increased 3x and month-end close shortened from 20 to 5 days.
Julia Stalnaya · COO, Kitrum
05 - Key Takeaways
What made the difference
Speed of close is a strategic asset. At 25 days, finance data was a post-mortem. At 5 days, it became a management tool. The CEO went from reacting to the past to steering the present.
Most finance chaos is an infrastructure problem, not a people problem. The existing team wasn't slow - they were doing manual work that should never have been manual. Removing the manual handoffs was enough to transform the function.
Unit economics is the unlock for margin in services businesses. Aggregate revenue growth was masking unprofitable contracts. Project-level P&L surfaced what aggregate reporting never would.
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