Manny Singh

[Manny Singh @khaalMS]

@TaliaGold @perplexity_ai 365% for Mag7 versus the 330% of the “founder” basket. Also this list from good old chatGPT

[Manny Singh @khaalMS]

@TaliaGold @perplexity_ai You would’ve been better off yet investing in Mag7. Which obv skews the data. Founder effect or simple tech effect?

[Manny Singh @khaalMS]

@jeffgrimes9 @theallinpod Think of what Google Docs did to Microsoft Word. It wasn’t “cheaper Word,” it was multiplayer + instant access.

What’s the equivalent for financial research and analysis? The wedge that makes people rethink their workflow?
Curious where @Perplexity_ai takes this!

[Manny Singh @khaalMS]

It’ll take more than graphing 7 charts instead of 6 to break the oligopoly of the Big 4 (Bloomberg, FactSet, Refinitiv, S&P).

Everyone grumbles about terminal pricing, but simply undercutting them on cost won’t do the trick either, especially when the new AI-native tools still miss basic but essential functionality like valuation multiples.

To win, you need kill shots. A handful of use cases that actually break the legacy platforms.

I have a few ideas — but I’m curious what others here think would qualify.

[Manny Singh @khaalMS]

Manually entering 7 tickers would be annoyingly cumbersome even if Bloomy GP W dis allow for it. The issue is the entire UI/UX is not built for conversational interaction e.g., “graph mag7 stocks YtD and summarize their performance divergence”). They’re probably working on it though.

[Manny Singh @khaalMS]

@jeffgrimes9 This is great- how is a “notable” price move defined? Is it relative to the market, or stocks own trading history (high beta stocks have higher volatility so will move around even in the absence of idiosyncratic news). Or do we just let the algo decide what constitutes notable :)

[Manny Singh @khaalMS]

Really interesting thread. A few clarifying points that might be helpful (seeing some misconceptions in the comments about Bloomberg and the broader financial data industry).

First, Bloomberg isn’t alone. FactSet, IHS Markit (now part of S&P Global), and Refinitiv (now part of LSEG) all run very similar businesses cleaning, structuring, and delivering financial data at scale. Each excels in different areas: derivatives, CDS, credit (IHS) macro (Ref) equities (Bloomy & FDS), etc. Collectively, these four players represent a ~$25B annual industry spread across more fragmented offerings and client bases (banks, long onlies, quants, hedgies etc), with Bloomberg contributing ~$10B.

Second, none of them “own” any of the data. SEC filings come from EDGAR or directly from issuers. Trading data is sourced from exchanges, which license it out. Sell-side research and estimates come from the brokers and banks. It’s all about infrastructure, not IP ownership. The real value lies in aggregation, reliability, standardization, and workflow integration. These firms aren’t selling raw data — they’re selling trust, latency, and usability. It’s a lot of plumbing, and that plumbing is worth $100B+ in cap.

Third, this model isn’t unique to finance. IQVIA in healthcare (~$15B revenue) and RELX (LexisNexis, Elsevier, etc.) in legal/scientific are great examples of companies that repackage third-party or public data and build high-trust data platforms around it.

Totally agree with the broader point though, these data intermediaries are extremely valuable but also ripe for disruption. New AI-native platforms could rewire how insight is produced and consumed, especially for smaller teams outside the bulge-bracket core.

TLDR: Excited to see where Perplexity takes this. There’s a lot of white space here for a new kind of intelligent, real-time data layer that doesn’t just aggregate, it reasons. You’ll need to reproduce some plumbing and fight market inertia though. Plus the incumbents are probably not sitting still either.

[Manny Singh @khaalMS]

Aravind — some quick thoughts here from someone who’s lived inside the machine for a while.

Bloomberg isn’t valuable because it connects you to analysts. Sell-side coverage and access to management are “pay-to-play” through brokers — Bloomberg just aggregates it. Pricing data comes from the exchanges. Compliance isn’t native either; firms still run their own.

Bloomberg’s real edge is that it’s been around forever, has verified and structured decades of trading data, and offers a cleaner, more usable front end than anyone else. That’s how Mike won against Quotron and Cron, and why Thomson Reuters & Factset who tried competing against him on price couldn��t really make a dent.

You’re right though — there’s no fundamental reason a terminal should cost $30K/year. The moat is historical and UX-driven, not structural. There’s real room for disruption here for sure.