Every supplier communicates differently
- ❌ The problem: One supplier sends structured emails, another sends PDF attachments, another writes everything in WhatsApp. No traditional software can read and understand all these formats.
- ✅ The solution: AI that reads and interprets messages in any format - email, PDF, image, WhatsApp - and extracts relevant information (dates, quantities, references).
📊 Typical result: Information from 50+ suppliers centralized automatically, regardless of how each one communicates.
References that never match
- ❌ The problem: The supplier calls it "REF-2024-A", you have it as "Model A 2024", the client asks for "that blue one from last year". Traditional software cannot match these variations.
- ✅ The solution: AI that does fuzzy matching between different references, understanding that "black oxford shoe 42" and "OXF-BLK-42" and "oxford black size 42" are the same product.
📊 Typical result: 95% of references cross-matched automatically, even with completely different nomenclatures.
PDF invoices nobody can process
- ❌ The problem: Every supplier has a different invoice layout. Manually extracting data from 200 invoices/month is impossible. Traditional OCR fails with varied layouts.
- ✅ The solution: AI that understands invoice context regardless of layout - finds values, quantities, references and dates even in never-before-seen formats.
📊 Typical result: 90% of invoices processed automatically, even from new suppliers with unknown layouts.
Detecting problems before they explode
- ❌ The problem: Supplier was slightly late 3 times in a row. Nobody noticed the pattern. The fourth time, it was a critical order.
- ✅ The solution: AI that analyzes communication history and detects risk patterns - increasing delays, tone changes, repeated excuses - before they become serious problems.
📊 Typical result: Risk alerts 2-3 weeks before critical problems occur.
Responding to clients with scattered information
- ❌ The problem: Client asks about order status. Information is scattered across 5 emails, 2 WhatsApps, and a spreadsheet. Takes 10 minutes to compile a response.
- ✅ The solution: AI that searches in natural language - "where is client Silva's order?" - and synthesizes information from all sources into a ready-to-send response.
📊 Typical result: Client responses in 30 seconds with complete, up-to-date information.
Production reports in chaotic formats
- ❌ The problem: Factory floor sends photos of handwritten sheets, WhatsApp voice notes, poorly formatted emails. Consolidating this into useful data is a nightmare.
- ✅ The solution: AI that transcribes audio, reads handwritten notes, interprets confusing emails, and organizes everything into structured, searchable data.
📊 Typical result: 100% of production records digitized and searchable, regardless of original format.
Next Step
These problems share one thing: they involve unstructured information that traditional software cannot process. AI changes that. Choose one problem to start.
