Basic PDF readers failed on messy scans. A new engine now turns complex bank reports into clean, structured tables for analysis.
An enterprise platform enables organizations to build custom AI agents for diverse workflows, processing large volumes of unstructured documents like scanned insurance forms and financial statements.
Customers frequently upload massive knowledge bases with mixed formats and variable quality, ranging from low-resolution scans to complex...
“It’s fast, the quality is good, and we can scale up and down depending on the level of quality we need.”
No-code platform for building and deploying enterprise AI agents.
Data framework and agentic OCR platform for building LLM-powered applications.
Stack AI's Document processing is part of this use case:
Related implementations across industries and use cases
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Legacy systems choked on 1,000-page medical files. AI now converts handwritten notes and 1970s scans into structured data.
Loan officers spent hours manually scanning 500-page guidelines. Now, AI retrieves exact policies to answer clients in minutes.
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Legacy systems choked on 1,000-page medical files. AI now converts handwritten notes and 1970s scans into structured data.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
Basic PDF readers failed on messy scans. A new engine now turns complex bank reports into clean, structured tables for analysis.
An enterprise platform enables organizations to build custom AI agents for diverse workflows, processing large volumes of unstructured documents like scanned insurance forms and financial statements.
Customers frequently upload massive knowledge bases with mixed formats and variable quality, ranging from low-resolution scans to complex...
“It’s fast, the quality is good, and we can scale up and down depending on the level of quality we need.”
No-code platform for building and deploying enterprise AI agents.
Data framework and agentic OCR platform for building LLM-powered applications.
Stack AI's Document processing is part of this use case:
Related implementations across industries and use cases
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Legacy systems choked on 1,000-page medical files. AI now converts handwritten notes and 1970s scans into structured data.
Loan officers spent hours manually scanning 500-page guidelines. Now, AI retrieves exact policies to answer clients in minutes.
Standard parsers couldn't read scientific charts. AI now extracts visuals into text, making hidden data searchable.
Legacy systems choked on 1,000-page medical files. AI now converts handwritten notes and 1970s scans into structured data.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.