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DVMT
Dell Technologies Inc
stock NYSE

Inactive
Dec 27, 2018
80.00USD-1.393%(-1.13)1,919,971
Pre-market
0.00USD0.000%(0.00)0
After-hours
0.00USD0.000%(0.00)0
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DVMT Reddit Mentions
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We have sentiment values and mention counts going back to 2017. The complete data set is available via the API.
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DVMT Specific Mentions
As of Aug 7, 2026 6:10:39 PM EDT (<1 min. ago)
Includes all comments and posts. Mentions per user per ticker capped at one per hour.
102 days ago • u/Zealousideal-Cry-962 • r/quant • financial_database_api_with_proper • Tools • B
Hi all,
We're a small team of financial analysts and devs building out a financial database API called [xfinlink](http://xfinlink.com). It currently covers end-of-day prices and fundamentals data on all US equities going back 30+ years. Real-time and intraday data is on the roadmap.
Here are the [docs](https://xfinlink.com/docs), how to [connect to Claude/ChatGPT/Grok via MCP](https://xfinlink.com/docs#mcp-claude), and how to [vibe code with the Python client](https://xfinlink.com/docs).
If you've ever tried to vibe code anything with financial data, you know the pain. The LLM hallucinates field names, the docs are 200 pages of PDF, the API returns inconsistent structures across endpoints, and you spend more time debugging the data than building your actual project. We built xfinlink specifically to solve this. The entire API was designed to be LLM-readable from the start. Six endpoints, consistent field names, a ready-made context prompt you can copy-paste into any LLM, and an MCP server so you can skip coding entirely and just chat with your data. Check out our [docs](https://xfinlink.com/docs) to see instructions for both approaches.
The other problem we're solving is entity resolution, which is critical for high-quality research. When tickers get recycled, most providers simply truncate the history of the preceding entity or incorrectly merge them, producing unreliable jumps in data. DELL is a good example. yfinance currently splices together three stocks — the original Dell Inc., a VMware tracking stock (DVMT), and the re-IPO'd Dell Technologies — into one continuous series under "DELL". xfinlink knows the difference and returns the correct entity for the correct time period, no matter which ticker you query. We spent months building out this resolution layer, and we hope it is helpful to you. All fundamental data are sourced directly from SEC filings. We are also actively expanding our database, so do keep a lookout on what becomes available in the near future.
There's a free tier (50 requests/day) to try it out. There are two paid tiers, Lite and Pro, both with 14-day, cancel-anytime free trial periods.
If you see any anomalous data while using xfinlink, or there are additional data that you need, please send us a message at [hello@xfinlink.com](mailto:hello@xfinlink.com) and we will take action as soon as possible. We want to build good data and your help would be highly valuable.
Thank you and happy researching!
—Xfinlink team
sentiment 0.98
102 days ago • u/Zealousideal-Cry-962 • r/quant • financial_database_api_with_proper • Tools • B
Hi all,
We're a small team of financial analysts and devs building out a financial database API called [xfinlink](http://xfinlink.com). It currently covers end-of-day prices and fundamentals data on all US equities going back 30+ years. Real-time and intraday data is on the roadmap.
Here are the [docs](https://xfinlink.com/docs), how to [connect to Claude/ChatGPT/Grok via MCP](https://xfinlink.com/docs#mcp-claude), and how to [vibe code with the Python client](https://xfinlink.com/docs).
If you've ever tried to vibe code anything with financial data, you know the pain. The LLM hallucinates field names, the docs are 200 pages of PDF, the API returns inconsistent structures across endpoints, and you spend more time debugging the data than building your actual project. We built xfinlink specifically to solve this. The entire API was designed to be LLM-readable from the start. Six endpoints, consistent field names, a ready-made context prompt you can copy-paste into any LLM, and an MCP server so you can skip coding entirely and just chat with your data. Check out our [docs](https://xfinlink.com/docs) to see instructions for both approaches.
The other problem we're solving is entity resolution, which is critical for high-quality research. When tickers get recycled, most providers simply truncate the history of the preceding entity or incorrectly merge them, producing unreliable jumps in data. DELL is a good example. yfinance currently splices together three stocks — the original Dell Inc., a VMware tracking stock (DVMT), and the re-IPO'd Dell Technologies — into one continuous series under "DELL". xfinlink knows the difference and returns the correct entity for the correct time period, no matter which ticker you query. We spent months building out this resolution layer, and we hope it is helpful to you. All fundamental data are sourced directly from SEC filings. We are also actively expanding our database, so do keep a lookout on what becomes available in the near future.
There's a free tier (50 requests/day) to try it out. There are two paid tiers, Lite and Pro, both with 14-day, cancel-anytime free trial periods.
If you see any anomalous data while using xfinlink, or there are additional data that you need, please send us a message at [hello@xfinlink.com](mailto:hello@xfinlink.com) and we will take action as soon as possible. We want to build good data and your help would be highly valuable.
Thank you and happy researching!
—Xfinlink team
sentiment 0.98


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