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Finance teams are being sold AI tools before the foundations exist — clean data, mapped processes, a single version of truth. We fix that first. Then we activate AI that actually works.
STARTED AT
30%
ACHIEVED
70%
Why most AI projects fail
AI is only as good as what you feed it. Most finance teams don't have clean, structured data — they have years of inconsistent spreadsheets.
You can't automate a process that hasn't been defined. Implementing AI on top of manual, undocumented workflows just automates the mess.
Adding an AI tool on top of a fragmented tech stack doesn't fix the underlying problem. It exposes it.
How we work
We implement and optimise CCH Tagetik — the EPM platform used by leading finance functions for consolidation and FP&A. The implementation itself builds the data foundation your finance team needs. AI capabilities are embedded in Tagetik natively — not layered on after the fact.
STEP 01
Data audit, process mapping, consolidation and FP&A readiness
STEP 02
CCH Tagetik deployment: financial close, consolidation, budgeting, forecasting
STEP 03
Embedded ML models, predictive forecasting, driver-based planning
IN PRACTICE
Prediction accuracy. 4 weeks.
A data-intensive organisation had spent years trying to forecast a core operational metric. They'd tried multiple statistical models. Accuracy had plateaued at around 30% — not enough confidence to act on.
We identified an out-of-the-box machine learning model in CCH Tagetik that could do exactly what they needed. The gap wasn't the software — it was the data. We sourced relevant external drivers from public datasets, combined them with their historical records, and ran the model. Within four weeks, accuracy reached 70%.
The proof of concept didn't just produce a better forecast. It showed the client exactly what they needed to scale it: a proper data foundation. That realisation became the start of a full EPM project.
Client identity withheld. Metrics verified internally.
What clients say
Using a collaborative approach, we deliver value-driven solutions, harmonising people, process, data and technology.
