Published: 13 December 2022
Summary
Insight engines deliver information in support of digital workplaces and data in support of analytics and automation. This Critical Capabilities report will help IT leaders choose the most suitable offering from a range of vendors.
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Overview
Key Findings
The application of insight engine capabilities to localized use cases requires custom development, which can be lengthy and challenging in the absence of productized solutions aligned with specific use cases.
Semantic search, which uses the relationships between words as well as the words themselves, is increasingly dependent on the use of machine learning (ML), which vendors are increasingly supporting in their products.
Optimizing relevant experiences depends on both personalization and the evaluation and tuning of relevance, but products’ capabilities vary significantly in this regard, with some products found wanting in respect of one or both capabilities.
Most products support cloud-based deployment,
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Strategic Planning Assumptions
- Coveo
- Elastic
- EPAM
- Expert.ai
- IBM
- IntraFind
- Lucidworks
- Micro Focus
- Microsoft (Azure Cognitive Search)
- Microsoft (Microsoft Search)
- Mindbreeze
- SearchBlox
- Sinequa
- S&P Global
- Squirro
- Squiz
- Analyze Result Sets
- Ingest Content and Data
- Deploy With Flexibility
- Extract and Enrich Content and Data
- Delivery to Various Touchpoints
- Evaluate and Tune Relevance
- Personalize Experiences
- Digital Workplace
- Website
- Applications
- Analytics and Automation
Gartner Recommended Reading
Critical Capabilities Methodology