After 8 months in production:

The Challenge

Fuse, a B2B SaaS company, helps enterprises automate repetitive document-heavy workflows. Their existing rule-based automation couldn't handle the complexity and variability of real-world business documents — invoices, contracts, forms, and reports in dozens of formats.

Their customers were struggling with:

Unstructured data — Documents arriving as PDFs, scans, and images with no consistent format

High error rates — OCR and template-based extraction failing on complex layouts

Manual validation — Staff spending hours checking and correcting automated extractions

Our Approach

We partnered with Fuse to build an AI-native document understanding system that could handle unstructured data at scale.

We analyzed Fuse's document corpus to understand the challenge:

We designed a multi-stage AI pipeline:

50,000+ sample documents across 12 document types

Identified common extraction patterns and edge cases

The Outcome

After 8 months in production:

60% reduction in manual data entry across customer workflows

1M+ documents processed in the first year

94.5% straight-through processing rate (no human intervention needed)

5x faster document processing vs. previous OCR solution

“"Selectcursor transformed our product from a basic automation tool into an intelligent system that actually understands documents. Our customers are seeing ROI within weeks, not months."”

Technologies Used