Oli Nold

Founder | Investor | Building Predictive Business Intelligence | Managing one of the Largest AI-Training-Grounds for Human Capital

[Oli Nold @olinold]

Workforce datasets are static.
A snapshot. A list. A moment in time.

But companies are not static.

They grow.
They contract.
They shift role composition.
They reallocate talent before revenue changes show up.

So instead of building another database, I built a longitudinal company-year panel.

~2.5M normalized U.S. companies.
~387M company-year rows reconstructed from historical experience timelines.
Median 7 years of workforce history per company.

Not profiles.
Not contact records.
Company-year intelligence.

For each company and each year:
• Observed headcount
• Growth rate
• Role distribution shifts
• Structured entity normalization

The real asset isn’t volume.

It’s the ability to ask:

– When did this company actually start scaling?
– Did engineering grow before sales?
– How did workforce composition change pre-funding?
– Which segments show consistent multi-year expansion patterns?

Longitudinal structure turns raw records into signal.

Investors call it alternative data.
Strategists call it market intelligence.
AI teams call it training infrastructure.

I call it organizational time-series intelligence.

Building this in public.

#infrastructure #database #patternrecognition

[Oli Nold @olinold]

@TejasGupta67820 I took my 3 dogs and moved to the backyard of Cyprus 🇨🇾. Can recommend 😎

[Oli Nold @olinold]

@hthieblot predictive intelligence for human capital and business evolution: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@i_mika_el ☎️

[Oli Nold @olinold]

@i_mika_el Simple, extracting patterns in a RAG to overlay on any system.
Or a parquet or API if the whole universe gets ingested

[Oli Nold @olinold]

@LoopandPixels building the predictive layer for business intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@heyblake building the predictive layer for business intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@FlippedRay building the predictive layer for business intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@SaidAitmbarek building the predictive layer for business intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@knowRowan building the predictive layer for business intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@JulieLabs8 weekend... what is it?

[Oli Nold @olinold]

@pcshipp the next startup...story of my life

[Oli Nold @olinold]

@kseniam0s @X Building predictive business intelligence: https://t.co/n9D0BVmlsO - your data room project looks interesting

[Oli Nold @olinold]

@RyanOlunix Building the predictive layer for Business Intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

@sflorimm Building the predictive layer for business intelligence: https://t.co/n9D0BVmlsO

[Oli Nold @olinold]

I create RAG files with knowledge…ever thought about this instead of just delivering data…?

[Oli Nold @olinold]

@clayolaaa If you put your last 20 dollars into a meme you have much bigger problems than only 5 dollars left

[Oli Nold @olinold]

It’s not that simple. It’s ether related to the leading coins or its a marketing gig. This one is a marketing gig. It goes when there is momentum. Ther was momentum, 4 months ago and then 4 days ago. Momentum only holds if a it gets nurtured. This one wasn’t. So people sell off.
Last spark of hope… they let it happen because some big boys want an entry. The next days will tell. From there it’s a gamble like every other coin with a few hundred k mcap.

[Oli Nold @olinold]

@Ling0Deg @ImCryptoGag If that’s the case why does it matter if the market is read

[Oli Nold @olinold]

@Ling0Deg @ImCryptoGag He’s absolutely right. Imagine you get your account back after 4 months, volume kicks in and then you do….absolutely nothing 🤣