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We have provided information on the cost of launching an MVP for three projects of varying levels of complexity, enabling you to compare what each project entails.
FAQ
What is the first AI use case that usually creates value without adding audit risk?
Start with evidence ingestion and classification: extracting fields from bills, invoices, and supplier docs, then mapping them to metrics. Keep provenance, require review, and lock versions. It saves time and improves completeness without letting AI invent numbers.
How do we stop "version drift" when the same metric appears in multiple reports?
Create one definition and calculation source of truth, then reuse it everywhere. Track boundary changes and factor updates as first-class events, with effective dates and change logs. If one number changes, every downstream output should update consistently.
What changes when you prepare for limited assurance, not just internal reporting?
You need reproducibility: evidence links, audit logs, access control, and a clear chain from source artifact to disclosure line item. Treat prompts, extraction rules, and taxonomies like controlled assets, and make every approval step explicit.
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