We build drones that pick items in e-commerce fulfillment centers

Hacker News

At Hummingbird Systems, we have developed a unique drone based approach to robotic warehouse unit order picking, especially well suited to direct-to-consumer e-commerce fulfillment. So why use drones? … Fundamentally lower cost. Hummingbird's drone platform is inherently less expensive than ground robots with pick arms or large gantry style AS/RS systems. The drones allow us to directly position the manipulator on task without all the weight and expense of multi-axis backlash free geared motor assemblies. Furthermore unlocking the often unused vertical real-estate in e-comm warehouses, the ability to leverage existing bins and racking, and a unique overhead tether power system that eliminates the need for batteries or recharging all contribute to the best ROI of any robotic picking solution on the market. Feel free to contact us if you have any questions, ideas for new use cases, or investment: http://hbird.tech

Visit product View on Hacker NewsDec 25, 2024

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Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · 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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