AI Automation for Finance

Unlock efficiency and accuracy with AI-powered automation solutions tailored for finance workflows.

Our AI Automation Solutions

We leverage advanced AI to transform manual finance processes into automated, intelligent workflows:

  • Automate outreach: capture → CRM → WhatsApp/Email → calendar booking.
  • AI parsing of PDFs/Excels (TB/BS/P&L) with reconciliation to ERP/ledgers.
  • Research copilots & document Q&A (RAG) for faster diligence prep.
  • Data pipelines to Looker/Power BI with anomaly alerts and scheduled reports.

Outputs & Impact

  • Custom n8n/Make workflows or lightweight Python services + runbook.
  • Document AI copilot + SOPs for enhanced efficiency.
  • Live dashboards with KPI alerts for real-time insights.

Timeline: Typically a 2–4 week pilot. Our solutions often result in 40–70% time saved.

Automate Your Finance Workflows

What we do on the engagement

Data ingestion and reconciliation

The step that eats most of a junior analyst's first week: loading, mapping and reconciling the trial balance to reported figures. We automate the repeatable parts so the analyst starts on analysis.

  • Trial-balance loading with automatic account mapping
  • Source-to-summary reconciliation with variance flagging
  • Multi-period standardisation of the chart of accounts
  • Foreign-currency translation where the reporting currency differs from the functional

Analytical schedules

The schedules that appear in every databook, built consistently across periods and engagements so the output is comparable and the build is not redone from scratch each time.

  • Monthly P&L and balance sheet at account level
  • Working capital by component with LTM average
  • Revenue analysis by product, geography and customer
  • Personnel cost tied to FTE with average cost derived

Quality control

Automation does not remove the need for judgement; it removes the need for a human to check that a formula has been copied correctly. We still review every output.

  • Cross-schedule tie checks that flag breaks automatically
  • Period-on-period variance thresholds that surface unusual movements
  • Adjustment evidence tracking so nothing is asserted without a source reference

Frequently asked questions

Does automation replace the analyst?

No. It removes the mechanical parts of the work so the analyst spends time on the parts that require judgement: whether an adjustment is supportable, whether revenue is sustainable, whether the working capital peg is defensible. The output is faster and more consistent; the thinking is still human.

What tools do you use?

We work in Excel and the Microsoft stack, because that is what buyers and their advisers use. We do not require you to adopt a proprietary platform.

Can we see the automation in action?

Our sample databook is built using the same automated schedules we deploy on live engagements. The structure is the same; only the data is synthetic.

Why this matters

Automation in financial diligence is not about replacing analysts. It is about removing the mechanical parts of the work so the analyst spends time on the parts that require judgement.

The problem we solve

On a typical engagement, the first week disappears into data loading, account mapping and reconciliation. The analyst is capable of analysis but is doing data entry. We automate the repeatable parts so the engagement starts on analysis, not on setup.

What we automate

Trial-balance loading with automatic account mapping. Source-to-summary reconciliation with variance flagging. Multi-period standardisation of the chart of accounts. The analytical schedules that appear in every databook, built consistently across periods. Cross-schedule tie checks that flag breaks automatically.

What we do not automate

Whether an adjustment is supportable. Whether revenue is sustainable. Whether the working capital peg is defensible. Those require judgement, and they get it. Automation handles the mechanics; a senior analyst handles the thinking.