AI for Finance, Reporting & Operations

Most stalled pilots have one of two root causes: fragmented data that the model can't work with, or a lack of trust and control that prevents anyone from actually deploying the output. We start with a frank diagnosis — what's stuck and why — then rebuild around the foundation that was missing. Often the original concept is sound; the surrounding scaffolding wasn't there.

No, but you'll get there faster if you sequence it right. Companies that standardise their chart of accounts and ERP first reach full automation in about 6 months; those with fragmented data need 12–18. We typically run the data foundation work in parallel with a contained, high-value pilot — proving value while the cleanup happens, rather than waiting for perfect data before starting.

Agentic systems in finance work inside a constrained environment — they read source data and propose actions, but they don't post unreviewed entries. Every action is traceable, every decision explainable, every output audit-ready. The AI does 80% of the work and flags the 20% that needs human judgement, rather than replacing the controls that keep your numbers right.

No. We build on top of what you have. Most of our work sits as a cloud AI layer over existing ERPs and legacy systems — the goal is to make those systems more useful, not to rip and replace. ERP standardisation helps, but it's not a prerequisite to start.

Tools solve a known problem with a fixed workflow. We build for the parts of your finance operations that don't fit a standard workflow — your specific deal flow, your specific close process, your specific reporting needs — and for the governance layer that makes any AI in finance defensible to auditors and regulators. We often work alongside off-the-shelf tools rather than against them, integrating them into the broader system.

The EU AI Act applies to most finance-related AI deployments, and we build for it as standard — risk classification, technical documentation, human oversight, transparency. Same for sector-specific frameworks (GDPR, MiFID II, AMLD, and GAMP 5 where life-sciences finance is in scope). Compliance isn't bolted on at the end; it's a constraint we design around from the first sketch.

Reporting and variance analysis is the fastest-paying use case — typically 3 to 6 months to value. Month-end close automation usually delivers in 6 to 12 months and can cut a 12-day close to 3. Larger transformations (AP automation, agentic deal flow, full compliance overhaul) run 12 to 18 months. We can scope concrete numbers for your situation in a first conversation.