108 Interest Score
11 Discussions
0.10 Engagement
May 2023 Launched

TiredBanker has taken 10 years-worth of earnings reports, and call transcripts and summarized them using GPT-4. We provide a weekly email digest containing new calls that took place, or you can peruse our comprehensive library of previous calls.

What the Community Said

Hello! I’m Sunil Rajaraman - I’ve been a serial entrepreneur/writer in the tech world for the past 10 years. I co-founded a writer marketplace called Scripted, and ran a local SF publication called The Bold Italic which I sold to Medium a few years back. Along the way I’ve invested in startups - both personally and as a Sequoia scout, and ran marketing at various companies (was CMO at Metromile, and VP of Marketing at GoodRx). Early in my career, I was a pure numbers guy. I spent time as an M&am

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Now THIS is an excellent use of GPT/LLM technology...! Looking backwards across a huge but uniform dataset to pull out insights that human analysts may not be able to spot simply because — how can a human keep so many variables in mind at one time? This use case is narrow, specific, and useful. Love it.

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Time to get back onto wallstreetbets 😆 But in all seriousness, this makes personal finance & investment knowledge a lot more accessible to people. Great launch ?makers!

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Congrats on the launch, Sunil! It would be super cool if a user was able to make specific questions against dataset, e.g. "what is common for all companies which grew their revenue at least 20% each quarter"?

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Love how easy it is to actually just understand a company at a high level! Looking forward to receiving the weekly digests… Is all the data shown about companies from LLM trained on the quarterly reports etc or, do you also plug into ‘real’ data sources?

— [REDACTED]

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Frequently Asked Questions

The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.

Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.

A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.

Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.

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