Parseur

Use Case 1: Automated Accounts Payable for Small Businesses

Problem: Small business owners and accountants often spend hours manually typing data from PDF invoices and receipts into accounting software like QuickBooks or Xero. This "busywork" is prone to human error and delays financial reporting.
Solution: Parseur’s AI engine can automatically detect and extract key fields such as invoice number, vendor name, tax amounts, and line items without needing to set up complex rules for every different vendor layout.
Example: A restaurant receives dozens of food supply invoices via email. They set up a forwarding rule to Parseur. Parseur extracts the data in seconds and uses a Zapier integration to automatically create a "New Bill" in their accounting software.

Use Case 2: Real Estate Lead Management from Property Portals

Problem: Real estate agents receive leads from various platforms (Zillow, Trulia, etc.) in the form of unstructured emails. Manually copying contact details and property interests into a CRM is slow, often leading to delayed follow-ups and lost sales.
Solution: Using the Text Parsing engine, Parseur can identify specific patterns in these automated emails to extract the lead’s name, phone number, and the specific property they are interested in.
Example: When a "New Inquiry" email arrives from a property portal, Parseur parses the text and immediately triggers a webhook that adds the contact to the agent's Salesforce CRM and sends an automated "Thank You" text via Twilio.

Use Case 3: Digital Marketing Competitor Tracking via Google Alerts

Problem: Marketers use Google Alerts to monitor brand mentions or competitor activity, but the resulting emails are cluttered with HTML and irrelevant text. Consolidating these alerts into a clean spreadsheet for weekly analysis is a tedious manual task.
Solution: Parseur can be configured to parse Google Alert emails specifically. It extracts the article titles, source URLs, and snippets, turning a messy email into structured rows of data.
Example: A marketing manager tracks the keyword "AI Data Extraction." Parseur processes the daily Google Alert emails and appends the extracted article links and dates directly into a shared Google Sheet for the PR team to review.

Use Case 4: Logistics and Bill of Lading Digitalization

Problem: Logistics companies frequently deal with scanned documents, such as Bills of Lading or shipping manifests, which are images rather than selectable text. Manually transcribing these documents into a tracking system is expensive and slow.
Solution: Parseur’s Zonal and Dynamic OCR (Optical Character Recognition) can read scanned PDFs and images, even identifying data that shifts position on the page. It can also handle handwriting, which is common in shipping notes.
Example: A warehouse clerk uploads a scan of a signed delivery note. Parseur’s OCR identifies the tracking number and the recipient's signature area, then updates the internal logistics database via Parseur’s REST API to mark the shipment as "Delivered."

Use Case 5: HR Resume Screening and Candidate Data Entry

Problem: HR departments receive hundreds of resumes (CVs) in various formats (PDF, Word, etc.) for a single job opening. Manually extracting contact info, skills, and work history to populate an Applicant Tracking System (ATS) takes days of administrative effort.
Solution: Parseur’s AI document parser can be trained to recognize common resume fields. Because it is "layout-aware," it can find the candidate's phone number or most recent job title regardless of how the resume is styled.
Example: Resumes sent to a "careers@" email address are automatically pulled into Parseur. The tool extracts the candidate's name, email, and LinkedIn URL, then pushes that structured data into a tool like Greenhouse or Workable via Power Automate.