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Bend 2.0 API for transaction enrichment/CO2e estimates

Hacker News

Bend 2.0 API for transaction enrichment/CO2e estimates

Heyy HN. We’re celebrating 2 years of Bend’s existence as a company and we’ve launched a new API to help you understand the climate impact of business activity, and/or embed climate data in your application. For most companies, 80% of your emissions are from the goods and services that you buy. Unless you’re running a power plant or an airline, odds are you’re not directly combusting lots of fossil fuels. But literally everything we buy has some upstream climate impact, whether it’s the flights and Ubers that we purchase, or our AWS bills (that run on grids powered by natural gas), all the way through to the computer / phone that you’re reading this on, in an office that is heated and cooled with some amount of coal, etc. And according to the Greenhouse Gas Protocol, all these indirect emissions count towards your company’s inventory (‘scope 3’ emissions). The problem is that figuring out how to estimate the emissions from all the thousands of things a company purchases is a hard data science problem. The best methodology may be different for any given item, and the relevant data is scattered all over the place. We’ve unified it under our v2 API. Here’s how it works: Transactions: For any financial transaction, we match the transaction vendor across our database of tens-of-thousands of vendors and return an emissions estimate based on the specific company’s climate profile, as well as any public decarbonization commitments or targets they’ve set. (There’s a big difference between $100 spent at Chevron vs $100 spent at Apple, for instance) Buildings: For your office (if you still have an office!) we use data gathered by the government and specific grid-intensity info, along with your square footage, to estimate the climate impact there. Flights: For flight route information we’ve wrapped a calculator created by the International Air Transport Association in a simple API. With the SEC set to announce new climate disclosure requirements in April, and more large companies requiring their vendors to report Greenhouse Gas inventories, Bend is on a mission to make it easy for any company to understand their climate impact. We hope you find it useful — we’d love your feedback! The Estimate APIs are 100% free and always will be; the Enrichment API is a paid service but includes a generous free tier of 100 API calls / month. And of course, our dream is that you’ll be inspired to plug this data into your stack, surfacing sustainability insights to your customers. You can get a trial key at https://bend.green/trial-key Thanks! - Ted & Thomas

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, computer, new · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: month, way · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, io · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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