Wall Street Prep
Built for world‑class investment research.
From source material to drivers, model, and written output. Primer is the AI analyst for equity investors.
Benchmarked performance
Proven on real analyst work.
Equity research is an output-quality problem. These benchmarks test Primer directly on real analyst work: modelling, retrieval, and full research tasks. Higher scores mean stronger research output.
See all the evalsFinRetrieval
Data retrieval
BigFinanceBench
End-to-end analyst work
Primer eval
Underlying cash flow
“This is the best thing we've used by some margin. We love it.”
Built by former analysts.
Primer was built by former analysts, so it understands what good research looks like: the standard of evidence, the level of detail, and the judgement calls that matter.
Takes on full research tasks.
Primer does more than return a single answer. Because it understands how analysts work, it can carry out multi-step research properly, from source material and data to drivers, model and written output.
Works autonomously across your coverage.
Set up recurring research tasks for the companies and questions you care about. Primer monitors, updates and flags what matters without waiting for the next prompt.
Compounds your context over time.
Primer learns your coverage, preferences and standards, so outputs become more useful as your research context builds.
Secure by default
Enterprise-grade by design.
Primer runs in the browser, includes the research sources analysts need, and is built with the controls institutions expect. Teams can use high-performance AI research without local setup, desktop installs or source-by-source permissioning.
- SOC 2 compliant
- Security controls and materials ready for institutional review.
- All in your browser
- No local setup, desktop install or handoff required.
- Sources included
- Primer includes access to the research sources it needs, so teams do not have to permission data source by source.
- Your data stays yours
- Customer data is ring-fenced and never used to train models.