Report:
The Forrester Wave™: Document Mining And Analytics Platforms, Q2 2024
How does Forrester define the Document Mining And Analytics Platforms market in 2024?
Document mining and analytics platforms enable enterprises to extract information from semi-structured documents and unstructured text within documents. Despite AI and generative AI advancements, the end-to-end process remains a challenging human-in-the-loop (HITL) process. For at least the next two to three years, document mining and analytics will remain the realm of specialist vendors offering platforms and/or solutions tuned for specific use cases. Generative AI is having immediate impact on vendor innovation in areas like conversational UI, where vendors can use off-the-shelf genAI models to interact with data extracted from documents. The market includes three core use cases: general purpose document/text mining, intelligent document extraction and processing (IDEP), and knowledge management, plus five extended use cases: contract analytics, information governance and data protection, digital process automation/robotic process automation, e-discovery, and investigative intelligence.
Key Facts for The Forrester Wave™: Document Mining And Analytics Platforms, Q2 2024 in 2024
- Publication Date: 29-May-2024
- Document ID:
- Summary: In our 25-criterion 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 technology, data, and automation professionals select the right one for their needs.
- Authors: Boris Evelson, Aaron Katz, Angela Lozada, Jen Barton
How did the Document Mining And Analytics Platforms market evolve in 2024?
- Generative AI is accelerating innovation in document mining and analytics, but human-in-the-loop (HITL) processes remain essential
- For at least the next two to three years, document mining and analytics will remain the realm of specialist vendors offering platforms and/or solutions tuned for specific use cases
- GenAI is having an immediate impact on vendor innovation in areas like conversational UI, where vendors can use off-the-shelf genAI models to interact with data extracted from documents
- The end-to-end process of mining information from semi-structured documents and unstructured text within documents remains a relatively challenging HITL process
- 14 providers were evaluated in this Forrester Wave assessment
- Vendors are categorized as Leaders, Strong Performers, Contenders, and Challengers
- Evaluation based on 25 criteria across current offering, strategy, and market presence
- Vendor materials evaluated as of March 12, 2024
What product features are required to be included in this year's evaluation?
- Overtly goes to market after at least two of the three core use cases for document mining and analytics as defined in The Document Mining And Analytics Platforms Landscape, Q1 2024: general purpose document/text mining, intelligent document extraction and processing (IDEP), and knowledge management
- Overtly goes to market after at least one of the five extended use cases as defined in The Document Mining And Analytics Platforms Landscape, Q1 2024: contract analytics, information governance and data protection, digital process automation (DPA)/robotic process automation (RPA), e-discovery, investigative intelligence for document mining, and analytics
- Demonstrates sufficient market presence as indicated by revenue (at least $10 million from document mining and analytics products) and interest from Forrester clients
What are the common features of top products in the Document Mining And Analytics Platforms space?
No common features specified.
Scope Exclusions
- Vendors that do not overtly market to at least two of the three core use cases (general purpose document/text mining, IDEP, knowledge management)
- Vendors that do not market to at least one of the five extended use cases (contract analytics, information governance, DPA/RPA, e-discovery, investigative intelligence)
- Vendors with less than $10 million in revenue from document mining and analytics products
- Vendors with insufficient interest from Forrester clients
- Pure-play RPA vendors without comprehensive document mining capabilities
- General-purpose analytics platforms without specialized document mining features
Inclusion Criteria
Vendors must, among other requirements:
- Overtly goes to market after at least two of the three core use cases: general purpose document/text mining, intelligent document extraction and processing (IDEP), and knowledge management
- Overtly goes to market after at least one of the five extended use cases: contract analytics, information governance and data protection, digital process automation (DPA)/robotic process automation (RPA), e-discovery, investigative intelligence for document mining, and analytics
- Demonstrates sufficient market presence as indicated by revenue (at least $10 million from document mining and analytics products) and interest from Forrester clients
Offering Strengths — Relative Weighting
- Accuracy verification — 6%
- AI: Knowledge-based or symbolic — 7%
- AI: ML-based — 7%
- AI: GenAI, pre-processing — 7%
- AI: GenAI, post-processing — 3%
- AI: GenAI — 5%
- AI: Document labeling for ML training — 7%
- Analytics — 4%
- Deployment options — 6%
- Automation — 6%
- Complex forms and images — 13%
- Cross document-level text mining — 2%
- DevOps — 3%
- Document-level text mining/NLP — 7%
- Globalization — 5%
- Security and regulatory compliance — 10%
- Support for all relevant use cases — 2%
Strategy Strength — Relative Weighting
- Vision — 25%
- Innovation — 25%
- Roadmap — 25%
- Partner ecosystem — 10%
- Adoption — 5%
- Pricing flexibility and transparency — 10%
FAQs
Q: What does this research cover?
A: This research covers a 25-criterion evaluation of document mining and analytics platforms providers. It evaluates 14 significant vendors across current offering capabilities, strategy, and market presence. The evaluation focuses on platforms that address core use cases including general purpose document/text mining, intelligent document extraction and processing (IDEP), and knowledge management, as well as extended use cases such as contract analytics, information governance, digital process automation, e-discovery, and investigative intelligence.
Q: Who should use this research?
A: This research should be used by technology, data, and automation professionals who are evaluating and selecting document mining and analytics platform providers for their organizations. It helps buyers understand how each vendor measures up across key capabilities, identify the right vendor for their specific needs, and make informed purchasing decisions in the document mining and analytics technology marketplace.
Q: What are the mandatory features of vendors included in this market?
A: Vendors must overtly market to at least two of three core use cases: general purpose document/text mining, intelligent document extraction and processing (IDEP), and knowledge management. They must also target at least one of five extended use cases: contract analytics, information governance and data protection, digital process automation/robotic process automation, e-discovery, or investigative intelligence for document mining and analytics. Additionally, vendors must demonstrate market presence with at least $10 million in revenue from document mining and analytics products and show significant interest from Forrester clients.
Q: What are some reasons for not being included in this report?
A:
- Does not market to at least two of the three core use cases for document mining and analytics
- Does not market to at least one of the five extended use cases
- Revenue from document mining and analytics products is less than $10 million
- Insufficient interest or inquiry volume from Forrester clients
- Declined to participate in the evaluation process
- Contributed only partially to the evaluation process
- Did not meet the materials submission deadline of March 12, 2024
Q: What should buyers consider when evaluating products in this market?
A:
- Prioritize vendors that emphasize UX for HITL accuracy verification and improvement rather than claimed accuracy benchmarks
- Look for intuitive dashboards, reports, and alerts that present processed documents with low confidence scores or rule violations
- Ensure the platform allows easy correction of extracted data and triggers automatic rule updates or ML model retraining
- Evaluate out-of-the-box industry- and business-domain-focused accelerators for faster time to deployment
- Consider ML models pretrained on specific document types (invoices, purchase orders, credit applications, insurance claim forms, regulatory reports)
- Assess linguistic rules and ontologies built to extract topics from customer communications
- Verify comprehensive enterprise-grade generative AI guardrails including input preparation, prompt engineering, and RAG architecture
- Ensure output guardrails scan for and eliminate improper or irrelevant content
- Evaluate deployment options that match your infrastructure requirements (cloud, on-premises, hybrid)
- Consider the vendor's partner ecosystem strength and breadth for implementation support
- Assess pricing flexibility and transparency to understand total cost of ownership
- Verify support for required languages and global deployment options
- Ensure compliance with relevant security and regulatory requirements for your industry
Q: How has the Document Mining And Analytics Platforms market evolved in 2024?
A:
- Generative AI is accelerating innovation but requires human-in-the-loop (HITL) processes and guardrails
- End-to-end document mining remains challenging and will continue to be the realm of specialist vendors for the next 2-3 years
- GenAI is commoditizing certain tasks like document categorization, long document summarization, and conversational interactions with extracted data
- Emphasis on UX for HITL accuracy verification and improvement is critical
- Vendor claims of document mining accuracy are less relevant than ease of verification and improvement
- Industry- and business-domain-focused accelerators are increasingly important for faster deployment and reduced project risk
- Enterprise-grade generative AI guardrails are becoming a key differentiator, including input/output guardrails and RAG architecture
- Low-code development is being challenged by some vendors who argue it limits scaling and customization
- Hybrid AI (combining knowledge-based/symbolic AI with ML-based AI) delivers better out-of-the-box precision and accuracy
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Current Offering evaluates each vendor's position on the vertical axis and indicates the strength of its current product capabilities, features, and technical implementation across 17 criteria including AI capabilities, analytics, deployment options, automation, and security. Strategy evaluates placement on the horizontal axis and indicates the strength of vendors' strategic direction across 6 criteria including vision for the market, innovation investments, product roadmap, partner ecosystem breadth, customer adoption levels, and pricing models. Market presence is reflected by the size of each vendor's marker on the graphic and assesses their overall market footprint based on revenue and number of customers.
Reference
- Forrester, The Forrester Wave™: Document Mining And Analytics Platforms, Q2 2024, 29-May-2024, ID
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