An AI equity research analyst, built on data you can trace.
We build automated market data pipelines and AI analyst tools that run inside your business, so your team spends its time on judgment instead of copying numbers between documents.
Two systems that work together.
Automated market data pipelines
Scheduled collection of filings, prices, estimates and economic releases from the sources you are licensed to use. Cleaned, checked and stored in one place your models and tools can read.
An AI equity research analyst
A tool that reads filings, transcripts and your own documents, extracts the figures that matter, and drafts first-pass notes with every number linked to its source. A person reviews and signs off before anything is used.
From raw sources to a reviewed draft.
- Collect
Pull filings from regulator databases, data vendors and company investor pages on a schedule.
- Check
Validate totals, flag outliers and reconcile against a second source.
- Store
Keep clean, versioned data with the source and time of every value.
- Analyze
Feed your models and let the AI analyst extract metrics and compare periods.
- Review
An analyst checks the draft against sources and approves, edits or rejects it.
- Deliver
Send approved output to your team by dashboard, document or email.
It does the reading and the first draft. Your people do the deciding.
The tool handles the time-consuming parts of research so an analyst can cover more companies with the same care.
- Reads filings and transcripts and pulls out revenue, margins, cash flow, guidance and risk-factor changes
- Builds structured tables with a link back to the page each figure came from
- Updates your models with new results and highlights what moved against the prior period
- Drafts first-pass notes in your house format with sourced figures and open questions marked
- Answers questions over the document set you give it, with citations to the passages it used
What changes during an earnings season.
| Task | Today, by hand | With the pipeline and AI analyst |
|---|---|---|
| Collect filings | Download and file each one | Collected automatically on release |
| Extract key figures | Retype from PDFs and tables | Extracted with page citations, analyst checks |
| Update the model | Paste in numbers, trace errors | Inputs refreshed, differences flagged for review |
| First draft | Start from a blank page | Draft with sourced figures and open questions |
| Sign-off | Analyst | Analyst, with the audit trail attached |
Describes the workflow only. Actual time savings depend on your sources and processes.
Controls come with every system we build.
Every figure traced
Each number links to its source document and retrieval time, so a reviewer can check it in seconds.
Human review gate
Nothing leaves the system without an analyst's approval. The AI drafts, a person decides.
Tested before use
We run the tool against past filings with known answers and measure errors before it touches live work.
Audit log
We record inputs, versions of the model and prompts, and who approved each output.
Licensed data only
We build on data you have the right to use. Vendor terms often limit storage and redistribution, and we design around them.
Confidential by design
Your documents and queries stay in your environment under access controls you set.
Teams that read a lot of filings and update a lot of models.
- Private equity and growth funds monitoring portfolio companies and screening targets
- Independent research and advisory teams that want more coverage without more headcount
- Corporate finance and strategy teams tracking competitors and customers
- Family offices and asset managers building an in-house research desk
Start with one use case, then expand.
- Scope
Pick one workflow, such as quarterly KPI tracking for a set of companies, and agree how success is measured.
- Prototype
Build the pipeline and analyst for that workflow and test it against past results.
- Deploy
Run it alongside your team's current process, with review on every output.
- Improve
Add companies, sources and report types once the first workflow is trusted.
AI tools can make mistakes, including misreading a table or inventing a detail, which is why every output is reviewed against its source. Output is for your internal analysis. If you plan to publish or distribute AI-assisted research to clients or the public, securities and advertising rules in your jurisdiction may apply, and we build review and disclosure steps into the workflow to help you meet them. We are not a law firm and recommend your compliance team approves the process.