Report:
The Forrester Wave™: Document Mining And Analytics Platforms, Q2 2026
How does Forrester define the Document Mining And Analytics Platforms market in 2026?
Document mining and analytics platforms (DMAP) are enterprise-grade solutions that extract, analyze, and process information from documents using various AI techniques. These platforms span capabilities including agentic AI, machine learning-based AI, generative AI, knowledge-based AI, natural language processing, model lifecycle management, document handling across any type and complexity, accuracy verification and improvement techniques, and integration capabilities. Despite the emergence of agentic AI, DMAP requirements for complex enterprise use cases remain too extensive to build from scratch, making this very much a 'buy' market where organizations are better served selecting proven providers than attempting to assemble equivalent capabilities, even with agentic AI assistance.
Key Facts for The Forrester Wave™: Document Mining And Analytics Platforms, Q2 2026 in 2026
- Publication Date: 29-May-2026
- Document ID: d3f836ce
- Summary: In our evaluation of document mining and analytics platforms providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps you select the right one for your needs.
- Authors: Boris Evelson
How did the Document Mining And Analytics Platforms market evolve in 2026?
- Agentic AI can accelerate prototyping and automate parts of document mining workflows, but cannot replace full DMAP platforms for complex enterprise use cases
- Forrester identified more than 100 requirements spanning various AI techniques, model lifecycle management, and ability to handle any document type
- DMAP remains very much a 'buy' market, with most organizations better served by selecting a proven provider than building from scratch
- DMAP vendors come from different market lineages including ECM suites, intelligent automation platforms, and knowledge management/search providers
- Vendors optimize for different outcomes based on their market heritage
- Eight providers evaluated: UiPath, Hyperscience, Iron Mountain, Hyland, Automation Anywhere, Rossum, OpenText, and EdgeVerve
- Leaders include UiPath and Hyperscience
- Strong Performers include Iron Mountain, Hyland, Automation Anywhere, and Rossum
- Contenders include OpenText and EdgeVerve
- Hyperscience achieved Customer Favorite status with outstanding customer feedback
- Most DMAP use cases require human-in-the-loop (HITL) for review, exception handling, and continuous correction
- Evaluation materials cutoff date was March 4, 2026
What product features are required to be included in this year's evaluation?
No mandatory features specified.
What are the common features of top products in the Document Mining And Analytics Platforms space?
No common features specified.
Scope Exclusions
- Productized DMAP offerings from professional services firms (except EdgeVerve due to its status as separate legal entity)
- Vendors without at least $10 million in annual DMAP revenue
- Solutions not available as standalone products with their own SKU and pricing
- Vendors without broad enterprise-level support and demonstrated track record
- Solutions that are solely free features within larger portfolios
- Vendors without significant mindshare among Forrester enterprise clients
Inclusion Criteria
Vendors must, among other requirements:
- Broad, enterprise-level support - vendor natively provides all core functions and has demonstrated track record for supporting large enterprises
- Substantial revenue in the market - at least $10 million in annual revenue from DMAP product in last four fiscal quarters
- Platform/solution available for purchase as standalone product with its own SKU and pricing
- Mindshare among Forrester's enterprise clients - frequently mentioned in inquiries, advisories, consulting engagements, and other interactions
Offering Strengths — Relative Weighting
- Agentic AI ops/architecture — 6%
- Agentic AI functionality — 6%
- Agentic AI integration — 6%
- Generative AI functionality — 7%
- Knowledge/rules-based AI — 7%
- ML-based AI — 2%
- Generative AI architecture — 6%
- AI model orchestration — 2%
- AI model lifecycle management — 2%
- Vectorization and hybrid RAG — 2%
- Generative AI guardrails — 2%
- LMs pretrained on multiple document types — 2%
- Business domain and industry specialization — 2%
- Document labeling/annotation — 3%
- UI and other techniques for accuracy verification — 6%
- Complex content/forms processing — 2%
- Document packages and separation — 6%
- Long document mining and analytics — 2%
- Document quality and validation rules — 5%
- Natural language processing (NLP) — 6%
- Deployment options — 6%
- Globalization — 6%
- Data privacy — 2%
- Data masking — 2%
- Platform breadth/supported use cases — 7%
Strategy Strength — Relative Weighting
- Vision — 30%
- Innovation — 15%
- Roadmap — 15%
- Partner ecosystem — 30%
- Pricing flexibility and transparency — 5%
- Supporting services and offerings — 5%
FAQs
Q: What does this research cover?
A: This research evaluates the top eight document mining and analytics platforms (DMAP) providers based on their current offering capabilities and strategic positioning. The evaluation covers more than 100 requirements spanning AI techniques (agentic AI, generative AI, ML-based AI, knowledge-based AI), model lifecycle management, document processing capabilities, accuracy verification techniques, deployment options, and platform breadth. It assesses how vendors handle complex enterprise use cases including different document types, HITL workflows, compliance requirements, and integration with broader automation ecosystems.
Q: Who should use this research?
A: Document mining and analytics platforms customers should use this research to inform purchase decisions by: 1) Starting with the vendor segment that matches their primary use case (ECM suites, intelligent automation platforms, or knowledge management providers), 2) Prioritizing human-in-the-loop (HITL) design and user experience for review and exception handling workflows, and 3) Considering architecture factors including LLM-agnostic capabilities, deployment flexibility (cloud, private cloud, behind-the-firewall), and support for air-gapped deployments in highly regulated environments.
Q: What are the mandatory features of vendors included in this market?
A: Vendors must natively provide all core DMAP functions for enterprise-level support, including various AI techniques (agentic AI, generative AI, ML-based AI, knowledge-based AI), model lifecycle management, ability to handle any document type of any complexity, techniques for accuracy identification and improvement, natural language processing, document handling and separation capabilities, validation and quality rules, deployment options, globalization support, data privacy and masking, and platform breadth to support multiple use cases.
Q: What are some reasons for not being included in this report?
A:
- Annual revenue from DMAP product below $10 million in last four fiscal quarters
- Lack of broad enterprise-level support or demonstrated track record supporting large enterprises
- Product not available as standalone offering with its own SKU and pricing
- Solution only available as free feature within larger portfolio
- Insufficient mindshare among Forrester enterprise clients
- Being a productized DMAP offering from professional services firm (with exception for separate legal entities like EdgeVerve)
- Not meeting vendor participation requirements during evaluation process
Q: What should buyers consider when evaluating products in this market?
A:
- Start with the vendor segment that matches your use case - align with category (ECM suites, intelligent automation platforms, or knowledge management/search providers) that best fits primary use case
- Prioritize human-in-the-loop (HITL) design - scrutinize HITL UX for reviewer intuitiveness, validation/correction speed, and queue/escalation/audit trail management
- Consider architecture, not just functionality - validate LLM-agnostic capabilities and deployment flexibility including air-gapped options for highly regulated use cases
- Assess whether platform supports strict data residency and isolation requirements
- Evaluate vendor's ability to handle documents of any type and complexity
- Consider vendor's approach to accuracy identification and improvement techniques
- Assess integration capabilities with existing enterprise systems
- Evaluate model lifecycle management capabilities
- Consider vendor's partner ecosystem and implementation support
Q: How has the Document Mining And Analytics Platforms market evolved in 2026?
A:
- Agentic AI can accelerate prototyping and automate parts of document mining workflows but cannot replace comprehensive DMAP platforms
- DMAP requirements for complex enterprise use cases span more than 100 requirements covering various AI techniques
- DMAP remains a 'buy' market with most organizations better served selecting proven providers than building from scratch
- DMAP vendors come from different market lineages (ECM suites, intelligent automation platforms, knowledge management/search providers) and optimize for different outcomes
- Most DMAP use cases require human-in-the-loop (HITL) for review, exception handling, and continuous correction rather than 100% straight-through processing
- Architecture considerations include LLM-agnostic capabilities and deployment flexibility (cloud, private cloud, behind-the-firewall, air-gapped)
- Consolidation of IDP into broader content, records, and automation platforms
- Integration of agentic AI for multiple platform capabilities while maintaining governance and auditability
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Strength of Offering (Current Offering) measures the vendor's position on the vertical axis and evaluates the technical capabilities and features of the current platform, including AI techniques (agentic, generative, ML-based, knowledge-based), model lifecycle management, document handling capabilities, accuracy verification techniques, NLP, deployment options, globalization, data governance, and platform breadth. Strength of Strategy measures position on the horizontal axis and evaluates the vendor's market vision, innovation capacity, product roadmap, partner ecosystem, pricing models, and supporting services - focusing on strategic positioning and future direction rather than current technical capabilities.
Reference
- Forrester, The Forrester Wave™: Document Mining And Analytics Platforms, Q2 2026, 29-May-2026, ID d3f836ce
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