Bridging the Structured Data Gap

AI models generate powerful insights, but their outputs present challenges for business applications:

• Raw outputs are often unstructured text without consistent formatting
• Business systems require predictable data structures for processing
• Manual parsing introduces errors and inefficiencies
• Development teams struggle to standardize AI outputs across applications

Without proper parsing, organizations face significant barriers to AI adoption, as technical teams must build custom parsing solutions for each use case, creating maintenance burdens and slowing innovation cycles.