AI that reads and analyzes documents to identify key terms, issues, or relevant content. It reduces the time and effort required for manual review of large document sets.
Use cases
5
Examples
5
Industries
3
Timeline
5 mo
Data updated 1 day ago
Adoption over time
Documented cases per month
By case publish month · completed months only
5 cases documented across 17 months (Mar 25 – Jul 26), peaking at 1 in March 2025.
AI Use Cases Hub
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
4.4Innovativeness4.4/5Advanced4.4/5 - Advanced. Compared with recent Bedrock assistant cases, this is more advanced because it combines graph memory, GraphRAG, and agentic orchestration for a security assistant rather than a simple chatbot or enterprise playground.
Trend Micro enhanced its Companion AI assistant in its Vision One security software with long-term and short-term agentic memory capabilities.The company used Amazon Neptune as a knowledge graph and experience layer to connect threat intelligence, alerts, investigations, and successful remediation patterns so analysts can get more explainable and personalized security recommendations.Trend Micro combined Amazon Bedrock, Amazon Textract, and Amazon Managed Streaming for Apache Kafka to orchestrate agentic workflows, clean and enrich user conversations, and feed metadata into the graph for long-term memory and correlation analysis.
4Innovativeness4/5Advanced4/5 - Advanced. Innovative use of combined Google Cloud Document AI, Vertex AI Search, and Gemini generative AI models to automate complex legal document review at scale.
OneUptime built an AI-powered legal document review system using Google Cloud technologies to accelerate contract analysis.The system ingests contracts using Document AI for OCR, indexes documents with Vertex AI Search, and uses Gemini for legal clause analysis, risk assessment, obligation extraction, and contract comparison.AI-powered analysis enables reduction of manual review time from days to minutes, focusing lawyers on high-skill judgment tasks.The platform includes a review dashboard integrating search results and AI-generated insights for streamlined legal workflows.
4Innovativeness4/5Advanced4/5 - Advanced. Deep Research is described as programmable, composable agent workflows with multi-step orchestration, web grounding via Bing Search, auditability/traceability, and integration into Azure Logic Apps and Azure’s agent platform.
Microsoft has announced the public preview of Deep Research in Azure AI Foundry, an offering that allows organizations to build programmable, composable AI agents for enterprise-scale research automation. The API and SDK-based platform integrates OpenAI's agentic research capabilities, brings web grounding with Bing Search, and is fully embedded in Azure's enterprise-grade agentic platform. Developers can automate complex research tasks, generate transparent, auditable outputs, and compose multi-step workflows across tools and agents. Deep Research is designed for integration with existing business applications and workflows, including Azure Logic Apps, and provides complete traceability and auditability for all research outputs—ideal for regulated industries. The system orchestrates a multi-step research pipeline leveraging the latest OpenAI models such as GPT-4 to clarify intent, scope tasks, ground research with Bing Search, and synthesize information into structured, compliant reports. Pricing is pay-as-you-go based on tokens. The preview is available for Azure AI Foundry Agent Service customers intending to embed research automation at the core of their digital transformation initiatives.The architecture enables triggering agents from anywhere—apps, workflows, or other agents—turning research into a reusable business service. Customer organizations can orchestrate multiple agents, automate reporting and notification, ensure compliance and observability, and ultimately embed research capabilities throughout their enterprise ecosystem.Initial industry interest is broad, spanning market analysis, regulatory reporting, analytics, and competitive intelligence, with a focus on security, flexibility, and integration potential.
Azure AI Foundry Agent Service customersGlobalPublic Sector
3Innovativeness3/5Differentiated3/5 - Differentiated. LegalFly adds domain-specific drafting/review, discovery, and anonymisation with automated compliance checks while being integrated into Teams and Office 365 workflows.
LegalFly is an AI-powered platform designed for legal professionals, law firms, and corporate legal departments. By integrating with the Microsoft ecosystem, including Teams and Office 365, LegalFly transforms traditional legal workflows by providing advanced tools for document drafting, review, discovery, and anonymisation. The platform leverages AI to highlight key points in legal documents, suggest revisions, ensure compliance, and automate the preparation and review of complex legal materials. Its discovery module automates the often tedious process of sifting through large volumes of documents, speeding up legal research and due diligence. Anonymisation tools help safeguard confidential information and support regulatory compliance. LegalFly aims to free up legal experts from repetitive manual tasks, allowing them to focus on strategic, higher-value work and improve client service. While LegalFly is built to serve clients throughout Europe, it is particularly relevant to Belgian and EU legal practices. Deployment is fully integrated within familiar Microsoft environments, enhancing productivity and collaboration.
4Innovativeness4/5Advanced4/5 - Advanced. Implements a RAG-powered, agentic legal review workflow ('Case Explorer') that integrates Azure OpenAI and Microsoft 365 Copilot to surface critical facts from thousands of pages for CPS staff.
The UK Crown Prosecution Service (CPS) partnered with NTT DATA to deploy a generative AI-based 'Case Explorer' system to automate and enhance the legal document review process. Leveraging Microsoft Azure OpenAI technology and Microsoft 365 Copilot, the solution addressed the challenge of handling vast volumes of legal documents that can extend to thousands of pages for a single case. This RAG-powered, agentic workflow system intelligently surfaces the most critical information, improving the speed, accuracy, and efficiency of reviews by legal professionals. This real-world implementation delivered notable productivity gains, transforming previously manual, time-consuming legal procedures at the CPS.
How many document review use cases are documented?
The AI Use Case Hub documents 5 real document review deployments across 3 industries, with 5 detailed company examples you can browse.
Which industries adopt document review the most?
Document review is most common in Legal (60%), Public Sector (20%) and Tech & Comms (20%).
Which countries lead in document review?
United States leads documented document review deployments, followed by Belgium and United Kingdom.
What technologies are used for document review?
Teams most often build document review with Azure AI, Azure OpenAI and Teams.
What AI capabilities power document review?
Across the documented deployments, the most common capability patterns are Agent (60%), RAG (60%) and Copilot (20%).
What results do companies report from document review?
Across the 5 deployments reporting outcomes, companies most often cite new product / capability (100%), risk & compliance (60%) and speed & agility (60%).
