Kompas AI vs Semantic Scholar
Compare research AI Tools
Deep research and report generation that iteratively analyzes hundreds of sources to produce structured briefs, citations and next-step recommendations.
Semantic Scholar is a free AI powered scholarly search engine from AI2 that helps you find papers authors and citation links, and it also provides a public REST API and Academic Graph data access for building research tools and analyses.
Feature Tags Comparison
Key Features
- Iterative multi-pass research that expands coverage and depth
- Citation management with links and confidence notes
- Thematic clustering and summaries for fast scanning
- Charts tables and key facts blocks in exports
- Workspace history and collaboration for teams
- Configurable scope length and aggressiveness settings
- Free scholarly search: Provides a free search experience for papers authors venues and citation relationships
- REST API access: Offers a REST API to explore publication data about papers authors citations and venues
- API license terms: Publishes an API license agreement that defines acceptable use and legal obligations
- Graph based discovery: Supports citation network exploration to trace influential works and related research paths
- Metadata retrieval: Enables programmatic metadata retrieval for building research dashboards and tools
- Citation linkage: Helps follow citations and references quickly to map a field without manual browsing
Use Cases
- Market landscape and competitor mapping with sourced claims and charts
- Vendor shortlist comparisons with pros cons and pricing notes
- Policy and regulatory summaries with citations to primary texts
- Technology reviews and architectures synthesized from docs
- Customer voice aggregation from forums reviews and QA sites
- Go-to-market briefs for new regions or segments
- Literature discovery: Find key papers and authors in a topic and expand via citation links to build a reading list
- Author profiles: Track an authors output and coauthor network to understand a research area faster
- Dataset building: Use API data to build a local dataset of papers and citations for analysis and visualization
- Trend analysis: Analyze venues and citation patterns over time to spot emerging topics and influential work
- Tool prototyping: Build a research assistant app that fetches paper metadata and shows related work automatically
- Teaching workflows: Use the free search interface in classrooms to demonstrate citation networks and discovery
Perfect For
analysts product marketers founders and consultants who need credible research summaries with citations and structured exports
researchers, students, librarians, data scientists, science journalists, developers building research tools, analytics teams studying scholarly trends, and educators teaching literature discovery
Capabilities
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