--- title: AI Document Intelligence and Data Extraction Services | Avinya Labs description: AI document intelligence by Avinya Labs: structured extraction, classification and confidence scoring over high-volume documents, with only exceptions routed to people. Over 80% less manual review. url: /service-pages/service-ai-document-intelligence.html --- [AI Development](/service-pages/service-ai-development.html) / Document intelligence # Document intelligence that sends only the exceptions to people. Structured extraction and classification over high-volume documents, with low-confidence fields routed to a person instead of every page. [Book a call](https://calendly.com/abbylester/30-mins-meeting) [See the work](/service-pages/service-ai-document-intelligence.html#solutions) [>80%Reduction in manual document review](/case-studies/enterprise-document-intelligence.html) [~70%Faster document prep](/case-studies/ai-workflow-automation.html) [~50%Faster review time](/case-studies/ai-legal-assistant.html) ## Document intelligence services. From unstructured files to structured, reviewable data. ### Document classification Sort incoming documents by type automatically before any extraction starts. ### Structured field extraction Pull the fields you need into a defined schema, ready for your systems. ### Confidence scoring Every extracted field carries a confidence level, so uncertainty is visible. ### Exception review queues Only low-confidence fields and genuine exceptions go to people. ### Rules engine hand-off Extracted data feeds deterministic business rules, as in our workflow automation platform. ### Citation-grounded search Search across document sets with answers traced back to the source page. ### Unstructured data ingestion Bring scattered files and records into one connected system. ### Audit trails Changes to extracted records are logged, so every value can be traced. ### Integration & export Structured output delivered into your existing tools through their APIs. ## How it works. An illustrative replay based on a delivered engagement, using sample data. ## Document AI we have shipped. Each result comes from a delivered engagement. AI · Document intelligence ### AI document intelligence Extraction and classification that sends only the exceptions to people. >80% less manual review Link: /case-studies/enterprise-document-intelligence.html AI · Workflow automation ### Workflow automation platform AI extraction feeding a deterministic rules engine, with consistency checks built in. ~70% faster document prep Link: /case-studies/ai-workflow-automation.html AI · Legal ### Research & review assistant Citation-grounded answers, each one traced back to its source document. ~50% faster review time Link: /case-studies/ai-legal-assistant.html AI · Insurance ### Full-stack AI platform for insurance Fragmented policy, claims and correspondence data connected into one structured workflow. ~2.5x faster processing Link: /case-studies/ai-platform-insurance-broker.html AI · Construction ### AI SaaS for fit-out & construction An AI SaaS platform from drawing to quotation, for English and Chinese-speaking teams. 5-stage connected workflow Link: /case-studies/construction-fitout-ai-platform.html ## Why teams automate document review. People review what matters instead of every page. ### Less manual review Structured extraction handles the routine documents end to end. ### Visible uncertainty Confidence scores show exactly which values need a second look. ### Consistent output The same document produces the same structured result every time. ### Faster turnaround Documents move on as soon as they are processed, not when someone gets to them. ### Traceable values Every field can be traced back to where it came from. ### Connected data Extracted data flows into the systems that use it, instead of into another spreadsheet. ## Have documents your team reviews by hand? [Book a call](https://calendly.com/abbylester/30-mins-meeting) ## From idea to production. Four stages, with a working version reviewed at each one. ### Discovery Map the document workflow, the systems and data involved, and what good looks like. Discovery notesDone - Document types and volumes - Fields and schema needed - Where review happens today ### Scope & architecture Agree the architecture, success measures and delivery milestones. Solution designDone - Extraction and classification design - Confidence thresholds - Review queue and integrations ### Build Build against real data, with a working version reviewed at each milestone. Working buildDone - Pipeline built on sample documents - Accuracy checked on real cases - Review at each milestone ### Ship & support Roll out to production with monitoring and a defined support window. Production rolloutDone - Production pipeline - Monitoring of exceptions - Defined support window ## Results from our document AI work. Each number links to the engagement it came from. >80% Reduction in manual document review Document intelligence → Link: /case-studies/enterprise-document-intelligence.html ~70% Faster document prep Workflow automation → Link: /case-studies/ai-workflow-automation.html ~50% Faster review time Legal AI assistant → Link: /case-studies/ai-legal-assistant.html ## Engagement models. Pick the shape that fits where you are. Ongoing ### Dedicated team A dedicated team that works as an extension of yours, from first release to scale. Fixed scope ### Project-based A defined scope, milestones and delivery date for a specific product or workflow. Advisory ### Consulting & advisory Architecture and readiness advice before you commit to a build. ## What our clients say. AI platform for an insurance broker > “Avinya Labs built our full-stack AI solution, delivering scalable infrastructure, optimized AI workflows, and a seamless user experience. Their expertise accelerated our launch and significantly reduced execution risk.” SandraProject lead, Insurance broker Result~2.5x Faster processing speed [Read case study →](/case-studies/ai-platform-insurance-broker.html) AI chatbot for a travel platform > “Avinya Labs built our AI travel chatbot … A highly capable team that delivers ahead of the curve.” LauraCo-founder, Travel platform [Read case study →](/case-studies/ai-travel-chatbot.html) ## Document intelligence FAQs. ### What is document intelligence? Software that reads documents, classifies them, and extracts the fields you need into structured data, flagging anything it is unsure about for a person to check. ### What happens when the AI is not sure? Each field carries a confidence score. Anything below the threshold you set goes to a review queue instead of straight into your systems. ### Which document types can it handle? Unstructured and semi-structured documents such as contracts, forms, filings and correspondence. We confirm your document types during discovery. ### Can it plug into our existing systems? Yes. Structured output is delivered into your tools through their APIs or a structured export. ### How do you handle our data? Access is scoped to what the system needs, with role-based permissions and audit trails where records change. We agree data handling during discovery. ## Ready to turn your vision into reality? Tell us the problem, the data, and where manual effort sits today. We'll map the path from MVP to scale. [Book a call](https://calendly.com/abbylester/30-mins-meeting) [See the work](/work/index.html) Or email [contact@avinyalabs.co](mailto:contact@avinyalabs.co)