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Metronome , a startup that helps software program company offer usage - based charge , has raised $ 43 million in a Series B backing round direct by NEA .
Existing angel Andreessen Horowitz and General Catalyst also participated in the financing , which brings its total amount raised to over $ 78 million since its 2019 inception .
Founded by Dropbox alumsKevin Liu and Scott Woody , San Francisco - basedMetronomesays it visualise a 6x addition in ARR last twelvemonth as more company transitioned from subscription to usance - based models , or a combination of both . Its customers include startups such as OpenAI and Anthropic and enterprise companies like Databricks and Nvidia . ab initio , Metronome worked with startups but last year expanded to the enterprise .
“ We were fortunate to see that growth during what was otherwise a tough year for SaaS , ” say Liu . “ caller have been cutting spend on ‘ nice - to - have ’ computer software , but we ’re visit as a core number one wood of revenue chance for our customers . The rise of AI has also been a big factor ( many AI companies are adopting usage - based models ) , as has the desire from companies to move away from double-dyed subscription and seat - based models to more hybrid and usage - base approaches . ”
Unsurprisingly , Metronome itself has a custom - establish mannequin .
The startup declined to reveal its rating , say only that “ it was a very levelheaded multiple above ” its Series A valuation .
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The draw for AI companies
Metronome claims to “ dramatically subjugate ” the technology investment required by companies for charge integration and maintenance .
“ We help squad set up products promptly , offer any pricing and streamline quote - to - cash work flow , all without applied science effort , ” say Liu . It does that with a information platform that it says offers integrations “ out - of - the - box , so engineering teams can just taper their information current directly at Metronome and skip having to own and exert a lot of their own base . ”
For enterprises in special , Metronome take that transitioning to swarm and/or utilisation - found revenue would typically ask overhauling their financial stack . Its product , Liu said , helps ease that transition “ while plugging into their existing tooling , minimizing to-do and drastically zip up the process . ”
AI company in particular seem to be drawn to Metronome ’s oblation , the ship’s company claims .
“ The entire AI stack has use - based COGS , from APIs down to the GPU infrastructure layer , which stand for that AI businesses often turn to use - ground pricing to keep their margins logical , ” said Woody . “ We ’ve had a vast amount of inward interest from companies look to monetize newfangled AI products . ”
Growing headcount
To facilitate meet that demand , over the last year , Metronome doubled its headcount to 66 full - prison term employee , grow its staff by more than 40 % in the last poop alone . It take to “ still have a hatful of hiring to do this year , ” particularly across its R&D and customer - facing teams .
The caller also contrive to use its new funding to pass on on its intersection roadmap .
“ This capital also move over us a tremendous amount of dry powder and rails , which is important in an changeable environment like this , ” said Liu . “ We ’re work up critical substructure , so customers need to experience that we ’ll be around for the longsighted haul . ”
As part of the funding rung , NEA partner Hilarie Koplow - McAdams has joined Metronome ’s board of director .
“ Billing is often under resourced internally and seen as a bottleneck for mathematical product launch and pricing changes . In reality , it ’s a make - or - break receipts number one wood for any business , ” she sound out in a pen statement . “ Metronome makes it potential for ship’s company to operationalize new business models quickly . Every customer we speak to share how Metronome turned charge from a ‘ hair - on - fervor ’ problem to a system that just works . ”
Metronome raise $ 30 M to help software companies shift to usage - based pricing model
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