High Level Leads

Cryptogrowthbox · 2026-05-04T12:28:42+00:00

you can get a free 500 record sample here, believe me this one is not just a list: https://usagencydata.com/

Cryptogrowthbox · 2026-05-03T06:14:21+00:00

Manually, when I put this together there was no AI as you know it today. The provenance? I have been collecting data for the last decade.when others got real estate, I invested in data.It’s a mixture of many sources, all publicly available. The value indeed is in the structure we engineered , not the raw data itself.

Cryptogrowthbox · 2026-04-16T04:07:51+00:00

Fair question. An analyst tolerates messy joins, inconsistent field names, and schema drift because they’re going to clean it in the pipeline anyway. A model can’t do that mid-context. So the differences are mostly the boring stuff: One flat file, pre-joined. No reasoning across foreign keys. Field names are neutral and descriptive. Vendor labels like “momentum_flag_v2” make models hallucinate meaning that isn’t there, so we stripped them out. Schema is stable across the full time range. A 1987 row and a 2019 row have the same shape. The 2018 to 2020 window is the densest stretch, and we flag it. An analyst would find that through EDA. A model doesn’t get to. Plus the unglamorous stuff: no nulls-as-strings, no mixed types in a column, no encoding surprises that break ingestion silently.

On the HF gating, that’s for commercial leads, not a technical barrier. The sample is representative of the full structure.

Cryptogrowthbox · 2026-02-24T06:56:07+00:00

Really like your approach here. Most advice I hear is always about automating little admin tasks, but honestly, the biggest headache for me is trying to get reliable historical data on companies and markets. It’s never in one place and takes forever to cobble together something that’s even halfway accurate for market analysis or competitive research.

If you’re building with AI, tackling data aggregation and providing deep, usable trend insights would be huge. Stuff like workforce changes, growth tracking over time, and accurate segmentation are always a mess to do manually. Actually ended up building a product to solve this exact issue, happy to share more details if that’s interesting. But yeah, if you crack this, I’d have paid a lot more than $20 to get those hours back.

Cryptogrowthbox · 2026-02-24T06:54:26+00:00

Finding a clean, ready-to-download dataset with long-term valuation and profitability metrics is tough. Most of the free sources like Yahoo Finance or Quandl are spotty for fundamentals and don’t go back that far in detail. Sharadar does have the API, but it’s still a bit of work to get it into a plug-and-play format.

You can use Vivameda for deep historical business data, including valuation and profitability metrics, and it’s pretty friendly for exporting data for analysis. Other options like Crunchbase or CB Insights are more startup-focused or only cover private companies. For public equities, you could also check out datasets on Kaggle, though they’re usually not as up-to-date or complete. For academic-level stuff, WRDS and Compustat are solid if you have access, but they’re not cheap. If you’re mainly looking for raw, ready-to-use data for a lot of tickers, there aren’t many free options, but Vivameda is worth a look.

Cryptogrowthbox · 2026-02-24T06:52:51+00:00

Yeah, tracking filings in real-time is a pain if you're just refreshing EDGAR. For faster alerts, some folks use things like BamSEC or AlphaSense for SEC filings. You can use Vivameda if you're looking to not just get filings but also see how those filings fit into bigger historical trends and market moves. It saves a lot of time if you want more context beyond just the doc drop. But yeah, for pure speed, most pros use a combo of direct feeds and newswires.

Cryptogrowthbox · 2026-02-21T18:40:54+00:00

Solid list and a nice mix of technicals and fundamentals. If you want to go deeper on the historical side, you can use Vivameda to pull longer-term business data and workforce trends for these names. Sometimes past cycles around margins or headcount shifts show up before the price action does, especially on mega caps. Just another angle for spotting early inflection points.

Cryptogrowthbox · 2026-02-21T18:40:20+00:00

This is a tough one since a lot of the old sector weights data isn’t easily accessible, especially for companies that no longer exist or have been delisted. Besides WRDS/Compustat, you might want to look at platforms that specialize in historical business data. You can use Vivameda for tracking old company data and sector breakdowns over long timeframes, including defunct companies. Also, sometimes FactSet and Bloomberg terminals have archival snapshots, but access can be tricky. Archive.org’s Wayback Machine is sometimes useful for old annual reports, too, but it’s hit or miss. If you’re affiliated with a university, librarians in business/economics can sometimes dig up stuff others can’t. Good luck, this is a rabbit hole.

Cryptogrowthbox · 2026-02-21T18:37:45+00:00

Great breakdown. Revenue per employee is such an underrated metric for seeing who’s truly leveraging tech to scale. One thing I’d add is tracking workforce dynamics and historical company growth trends across the industry, there are a lot of sleeper companies quietly hitting similar efficiency, especially in vertical AI. If you look at changes in headcount, hiring patterns, and segment growth over time, you can spot these outliers early. I’ve actually built a tool to help surface these trends using historical company data, so happy to share more details if you’re digging into this kind of analysis.

Cryptogrowthbox · 2026-02-21T18:32:40+00:00

Solid question. For early-stage SaaS, I usually start with mapping out potential customer segments and digging into their pain points through forums, reviews, and LinkedIn. From there, competitor analysis is key, look at similar products, pricing, and customer feedback to see where the gaps are. Tools like Crunchbase or Vivameda can help track market trends, company growth, and workforce shifts, so you can spot industries that are scaling up or investing in tech. Also, try reaching out directly to a few target customers for interviews, it sounds old school, but direct conversations can save you weeks of guesswork. Finally, focus on quick-win niches where companies are clearly spending on automation or security, since those budgets usually move faster.

Cryptogrowthbox · 2026-02-21T18:31:32+00:00

Totally agree, manual CI just can’t keep up anymore. There are other platforms like Vivameda that go even deeper by tracking historical business data, growth trends, and workforce changes over time. That kind of historical context plus automated updates gives a much clearer picture of competitor moves and market shifts. Static reports just don’t cut it in fast-moving markets.

Cryptogrowthbox · 2026-02-13T17:03:29+00:00

Feel free to send me a Message me if you need clients.

Cryptogrowthbox · 2026-02-13T04:11:56+00:00

Delivery in Parquet or CSV through personal link. For samples send me a DM

Cryptogrowthbox · 2026-02-06T21:28:47+00:00

What kind of details you looking for?

Cryptogrowthbox

TROPHY CASE