TESRAC features
TESRAC features for cached deep research
TESRAC combines cache-first report discovery with live AI deep research controls so users can reuse existing work when possible and tune fresh runs when needed.
Feature list
- Search cached deep research reports before starting a new live run.
- Query autocomplete and cached report suggestions after users type.
- Economy, Standard, and Deep research modes for different cost and depth needs.
- Balanced, verified, and fresh source strategies.
- Specialized prompts for technical, buying, civic, business, science, and general research.
- Adversarial review passes that challenge weak claims and missing caveats.
- Shareable cached report links and crawlable public sample outputs.
Why these features matter
Cached report suggestions reduce duplicate research. Research modes help control cost and depth. Source strategies make freshness and evidence quality explicit. Specialized prompts route different types of questions toward more relevant research angles.
More resources
- All resources
Browse the cached deep research resource library. - Deep research glossary
What deep research means, how it differs from normal AI research, and when a source-backed synthesis is worth the extra time. - Cached deep research
Why cached deep research reports help people avoid repeating expensive AI research work. - Deep research cost
How search calls, source scraping, model passes, and depth settings affect the cost of a live deep research report. - Deep research vs AI search
When a quick AI search is enough and when multi-step research, review, and synthesis are more useful. - TESRAC features
A feature overview for TESRAC's cached deep research workflow.