CASE STUDY · DOCUMENT AUTOMATION
Automating the Pre-Accounting Layer for Small Businesses
Turning scattered invoices, bank exports and supplier portals into one structured pre-accounting workflow — AI-assisted, source-linked and review-ready.
The situation
Small businesses often lose time before accounting even begins: invoices are scattered across inboxes, supplier portals, paper mail, bank exports, credit-card statements and spreadsheets. For many of them, accounting preparation is still highly manual — financial documents arrive through multiple channels, bank data has to be checked separately, and tax-advisor handovers depend on folders, spreadsheets or portal uploads.
The challenge is not only extracting invoice data. The real challenge is creating a reliable workflow that connects documents, payments, categories, source files and review steps.
What we built
We developed an AI-assisted solution for pre-accounting preparation, built on AWS, MongoDB, Airtable, automation tooling and LLM-based extraction workflows. The work covered the full intake-to-handover path:
- Invoice intake from different document sources
- Schema-based invoice extraction, with benchmarking of large language models
- Structured data storage and document/transaction matching
- A serverless backend architecture
- A no-code interface for review and validation
- Preparation of structured outputs for accounting handover
Business value
For small businesses, the value lies in reducing the hidden administrative effort around accounting preparation. Instead of manually collecting invoices, matching payments, checking folders and preparing handovers, financial documents can be gathered, structured, linked to source records and prepared for review in one workflow.
This creates clearer financial oversight, reduces repetitive manual work, lowers the risk of missing documents and makes collaboration with tax advisors more efficient. The benefit is not fully automated accounting — it is a cleaner, faster and more reliable preparation process before formal accounting begins.
Why this matters
This example shows how messy administrative workflows can be turned into structured AI-assisted systems. The same approach is relevant wherever business-critical information is scattered across documents, portals, emails, spreadsheets and manual processes.
Transferable relevance
The work is relevant for organisations that need to structure document-heavy workflows:
- Invoice and payment processing
- Funding documentation and procurement records
- Compliance evidence collection and audit preparation
- ESG data preparation
- Operational reporting and tax-advisor / external-partner handovers
KEY TAKEAWAY
Messy administrative workflows become structured AI-assisted systems when intake, extraction, matching and review are designed as one connected process.
NEXT STEP
A similar initiative?
In the free initial call we clarify whether Kernity is the right partner for your situation – and which entry point would make sense. The goal is not to sell a solution on the spot.
30 minutes · video or on-site · no preparation needed