An AI agent team collects, reads, analyses and benchmarks the investor reports for 50+ retail and consumer brands. It separates the talkers from the ones actually shipping. Every claim cited, or refused.
50+ companies · 150+ investor reports · Updated on earnings day · Engine open source, MIT
A single number quietly rewards companies with good investor relations writing. Split the axes and the interesting ones show up.
Vertical axis: AI use cases confirmed in production. Read the full scoring method → · See where your company lands →
Every field carries a source URL and an evidence tier. Ask Rachel something the corpus cannot answer and she says so and stops. An ungrounded claim is a bug, not a style note.
The same 27 fields for every company, so you can compare side by side instead of reading five reports.
No vendor funding, no paid placements, no sponsored scores. The engine is MIT licensed, so you can read the code that produced the number.
A profile tells you where one company stands. The rest of Rachel reads the week for you: what actually moved, the pattern repeating across the sector, and the stat or smart topic worth opening your next meeting with.
Two chapters, the same shape for every company. First the investor snapshot, always the latest reported period with the trend against the last full year. Then the company AI: what the board committed to, which use cases are confirmed live, and whose stack they run on. Free to browse.
Rachel started as a tool I needed and could not buy: knowing which AI is actually shipping across a sector, not just the accounts in front of me. By hand, that is an analyst month a quarter.
So I built a swarm of agents to do the reading. One watches the investor pages, one extracts each filing, one scores, one refuses to answer when the evidence is thin.
Rachel does not replace your analyst. She reads so your analyst has more bandwidth to think. Rachel's A-team of agents finds and digests the news as it lands. Humans using Rachel interpret what it means, how it influences or inspires your own AI strategy, what to use and what to leave.