WhappScan VS Gitql

WhappScan's answer

Most document extraction platforms assume everyone involved will log into a dashboard and upload files. That works inside one company and breaks the moment documents come from outside it — which is exactly the situation of an accounting firm, a property manager or a logistics operator.

• No adoption barrier. Anyone who can send a WhatsApp can feed the system.
• Your fields, not ours. Templates are defined per document type, so a Spanish supplier invoice can return taxable base, VAT, withholding and supplier tax ID as separate fields rather than a generic blob.
• Try before signing up. A free tool extracts a real document with no account and no card, so you can judge the output before committing.
• Web and WhatsApp in parallel. Both feed the same templates and the same export, so you are not locked into one input method.

WhappScan's answer

Small and mid-sized businesses that receive documents from many different senders, in inconsistent formats, and process them by hand.

• Accounting and bookkeeping firms handling supplier invoices, receipts and quarterly VAT filings for dozens of clients.
• Property managers and vacation-rental operators collecting guest ID documents for legally mandated traveller registration, plus utility invoices across multiple properties.
• Logistics, insurance and legal firms processing delivery notes, policies and case documents.

The common thread is that documents arrive from third parties who will not install software — so the bottleneck is data entry, not the lack of a database.

WhappScan's answer

WhappScan is the only document data extraction tool built around WhatsApp as the input channel. You forward an invoice, a receipt, an ID card or a business card to a WhatsApp number and get structured data back — no app to install, no account for the person sending it, no training.

Two things follow from that:

• Your clients never onboard onto anything. The accountant's client, the property owner, the driver — they already use WhatsApp every day. Adoption is the hardest part of document automation, and this removes it entirely.
• Extraction is template-driven, not model-driven. You define which fields matter for your documents and the AI fills them, so the output matches your process instead of a vendor's fixed schema. An AI assistant builds the first template from a plain-language description.

Results export to Excel, CSV, JSON or an API, and there's a free tool that runs without an account.

WhappScan's answer

WhappScan started from a simple observation while automating document workflows for small businesses: the technology to read an invoice had already been solved, but the projects still failed. Not because extraction was inaccurate — because nobody could get suppliers, clients or drivers to use the tool.

The pattern repeated everywhere. A firm would buy a document capture platform, and then keep receiving invoices by WhatsApp anyway, because that is where the conversation already happened.

So instead of asking people to change channel, the product uses the channel they already use. The extraction pipeline runs on AWS with configurable per-document templates, and WhatsApp is simply the front door. The web app exists for the people who prefer uploading, but the WhatsApp number is the reason it gets adopted at all.

WhappScan's answer

• Backend: AWS serverless — Lambda (Node.js), API Gateway (REST and WebSocket), DynamoDB, S3 and SQS, running in eu-north-1.
• Extraction: AWS Textract for OCR, combined with large language models for structured field extraction against user-defined templates.
• Frontend: React single-page applications, TailwindCSS.
• Messaging: WhatsApp Business Platform (Meta Cloud API).
• Billing: Stripe, for subscriptions and credit packs.