Earthboi | Explore Climate Data with AI

Other models know the method.
Earthboi has the data.

We gave Earthboi, Claude Opus 4.8 and ChatGPT (GPT-5.5) the same questions a weather trader actually asks. All three knew the method. Only Earthboi could reach the data and finish the job.

Earthboi

ClaudeOpus 4.8

ChatGPTGPT-5.5

Reached real climate data

Earthboi✓Real ERA5 data, pulled live

ClaudeNo — built a synthetic series

ChatGPTNo — blocked, or a coarse monthly proxy

Returned a usable number

Earthboi✓ Priced, solved and settled

ClaudeNumbers, but from a synthetic series

ChatGPTEstimates or scripts — “not settlement-grade”

Can you check the work?

Earthboi✓ Full audit trail, JSON/CSV export

ClaudeNo audit trail — a script at best

ChatGPTNo audit trail — a script at best

Time to answer (pricing test)

Earthboi~1 min

Claude~3 min

ChatGPT~6 min

What each tool actually did

Earthboi

Real workflow: ERA5 pull → 56 winter HDD settlements → burn + Monte Carlo pricing

ClaudeNo climate-data access; builds synthetic seasonal HDD

Claude Opus 4.8 response: it does not have live access to 30+ years of daily Heathrow temperature records, so it builds the pricer on a synthetic seasonal HDD series and calls the resulting numbers illustrative ballparks.

“…the numbers below are therefore illustrative ballparks.”

ChatGPTCoarse monthly proxy; not settlement-grade

ChatGPT GPT-5.5 response: the Met Office public Heathrow station file is monthly, so its burn-cost pass is a monthly-mean approximation to daily HDD18, not a formal exchange settlement series.

“…monthly-mean approximation … not a formal exchange settlement series.”

In plain terms: the question was to price a winter weather contract on London Heathrow, and answering it starts with the airport’s real temperature record. Earthboi pulled that record, built the index, priced the contract, and made every step downloadable. Claude and ChatGPT couldn’t reach it — one built a synthetic series, the other used a coarse monthly stand-in — and both said so themselves.

Tested August 2026 across four workflows: weather derivatives pricing, an eight-city European gas weather book, a Chicago O’Hare cold-winter hedge, and nine-county corn yield correlations — the last comparing Earthboi and ChatGPT only. Earthboi used ERA5 reanalysis at the named stations, not exchange settlement data; figures illustrate capability, not quotes. Competitor responses shown as returned.

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Other models know the method. Earthboi has the data.

Other models know the method.
Earthboi has the data.