Documind
Documind is a document intelligence platform that converts unstructured documents like invoices and purchase orders into structured, validated data using multiple vision-language models that cross-check each other's outputs. The platform assigns confidence scores to every extracted field, automatically flagging uncertain values for human review while high-confidence data flows directly into ERP, CRM, or RPA systems. It is designed for teams in trade, logistics, and finance who need reliable extraction across unpredictable document layouts without template maintenance.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Enterprise Software
- Software Only
Funding
Founders
Product
Problem
Traditional document processing tools rely on template-based OCR that breaks when new layouts, scanned copies, or phone photos arrive, requiring constant maintenance and manual re-keying. Single language models can return confident but incorrect answers, and misread fields in trade and logistics can cause delayed shipments or audit failures.
Solution
Documind runs multiple vision-language models in parallel, composes and cross-validates their outputs, and assigns a confidence score to every extracted field. Users define their desired output once as a plain-language schema, and the platform handles ingestion, extraction, and validation for every subsequent document. High-confidence values flow directly into existing systems, while uncertain fields are flagged for quick human review. The platform includes evaluation agents that run automated tests against curated document sets, providing granular accuracy metrics for every field and document type.
Target Audience
Primary customers are operations and finance teams in trade, logistics, and related industries that process high volumes of invoices, purchase orders, and other documents with unpredictable formats and need reliable, auditable extraction.
Features
- Multi-model ensemble approach running vision-language models in parallel with cross-validation and disagreement detection
- Confidence scoring for every extracted field with direct document references and reasoning for each decision
- Plain-language schema definition that lets users specify output structure without code
- Automated evaluation agents that generate ground truth, verify with humans, and score extraction quality per field
- Human escalation workflow that flags uncertain fields or model disagreements for review
- ISO/IEC 27001 certified with GDPR and KVKK alignment, SOC 2 Type II attestation in progress, EU and AU data residency endpoints, zero data retention agreements, SSO/SAML, and role-based access control
- Integrations with SAP, Salesforce, HubSpot, UiPath, Zapier, Make, n8n, and Airtable plus a REST API