Summary
AI research assistant for comparing earnings-call themes and searching transcripts with cited summaries.
About
Corpusense applies AI to earnings-call transcripts, helping financial researchers compare company and quarterly themes, search source material, and review summaries with transcript citations.
Corpusense supports earnings-call research across companies and quarters. It enables users to identify themes across calls, search a full transcript corpus, and generate analyst-grade summaries. Each claim in a summary is cited to the relevant transcript.
Key Features
Cross-company and cross-quarter theme analysis
Search across a full corpus of earnings-call transcripts
AI-generated analyst-grade summaries
Transcript citations for claims in summaries
Real-World Use Cases
Company and sector research
Compare themes in earnings calls across companies and quarters to support research on business performance and sector developments.
Transcript investigation
Search a collection of earnings-call transcripts to locate relevant discussion for a research question.
Evidence-backed briefing preparation
Use cited summaries to prepare research notes or briefings while retaining links between claims and transcript evidence.
Business Opportunities
Accelerate investment research workflows
Problem: Analysts may need to review many earnings-call transcripts to identify recurring themes and company-specific developments.
Solution: Use corpus-wide search and cross-company or cross-quarter theme analysis to focus review, with cited summaries for source verification.
Estimated ROI: Potential time savings in transcript discovery and synthesis; financial return depends on adoption, research volume, and the quality of resulting decisions.
Execution: Incorporate the tool into earnings-season research workflows; use search and theme analysis to identify relevant calls, then verify cited claims against the transcripts.
Support financial research products
Problem: Research teams and financial information providers need efficient ways to organize and analyze earnings-call content across companies and reporting periods.
Solution: Apply full-corpus search and cited AI summaries to make transcript research more accessible and traceable.
Estimated ROI: Potential improvements in research throughput and information access; ROI cannot be quantified from the available product information.
Execution: Evaluate the tool against existing transcript research processes and integrate it into analyst workflows where corpus search and source-backed summaries are useful.