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Document Intelligence Provenance API
5 Signals+2

Document Intelligence Provenance API

An API that extracts structured, schema-mapped data from PDFs, spreadsheets, emails, and CRM notes with field-level provenance.

Added May 30, 2026

Job Ads
Document AI
Data Infrastructure
Enterprise Automation
Opportunity Score
Opportunity: Medium (54%)
Evidence Strength
Vol: 30%
Urg: 50%
Spec: 100%
Market Analysis
high
$ high
Multi-billion dollar enterprise data automation market spanning document AI, OCR replacement, revenue intelligence, logistics automation, and AI data infrastructure.
The Problem

Enterprises still rely on critical data trapped in unstructured documents, conversations, and legacy systems. Existing OCR and parsing tools often fail on complex layouts, inconsistent schemas, and cross-system entity matching, leaving teams to build expensive custom extraction pipelines.

Potential Solution

Build a document intelligence platform that combines vision-based parsing, intelligent schema mapping, entity resolution, and provenance tracking. Teams can ingest messy files and conversational records, define target schemas, and receive structured outputs with source citations, permissions-aware retrieval, and audit-ready confidence metadata.

Why Now?

AI teams are increasingly building production agents and automated workflows, but those systems need reliable structured knowledge from messy enterprise data. Job postings show companies hiring platform, inference, and applied science teams specifically to solve extraction at scale.

Showing 1-19 of 19 signals

Senior Data Engineer
metriportJul 30, 2026

Building the ingestion path for customers pushing large volumes of their own data into the platform. Building document-processing pipelines that extract structured data from PDFs, images, and free text to feed ML models.

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Staff Data Engineer
metriportJul 30, 2026

Designing the ingestion path for customers pushing large volumes of their own data into the platform. Building document-processing pipelines that extract structured data from PDFs, images, and free text to feed ML models.

#SGunited Jobs AI & Data Science - Entry Level positions
itcan-pte-limited-200413557mJul 13, 2026

Design, build, productionize, and support scalable document parsing and content extraction pipelines on a modern hybrid cloud platform, handling structured and unstructured data including PDFs, PPTX, Excel, Word, images, scanned documents, videos, audios, charts, tables etc

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AI Software Engineer
mighty-bear-gamesJun 29, 2026

Document Intelligence at Scale: Engineer robust pipelines to extract and reason through unstructured data. You’ll be turning chaotic paperwork into a clear, strategic roadmap for the user’s recovery. Responsible & Reliable AI: In a regulated domain where correctness matters, you will establish the evaluation and monitoring frameworks that ensure our AI outputs are accurate, trustworthy, and empathetic.

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Solutions Engineer
reductoJun 29, 2026

The vast majority of enterprise data — from financial statements to health records — is locked in unstructured file formats like PDFs and spreadsheets. We train vision models to read those documents the way a human would, and make it possible to build products, train models, and automate processes at scale.

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+16 more signals