GoKawiilJust a year ago, most of the systems we talked about with our customers were familiar. Things like payments, onboarding, and fulfillment. Now, the stakes are higher. Customers are asking to run agents that work for days, weeks, or months, and this is becoming the new normal. When the scale changes this much and the work runs this long, how do you keep it reliable?
This funding round is what helps us continue to solve that problem.
Today we're excited to announce a $550M Series E at a $12.55B valuation, co-led by Lightspeed, with Wellington Management, Growth Equity at Goldman Sachs Alternatives, and Tiger Global, with strong participation from T. Rowe Price and SV Angel. Returning investors include a16z, Sequoia, Index, GIC, Sapphire Ventures, and Amplify.
The problem is one we share #
AI is making customers expect an application to do so much more, all while the systems underneath are getting more complex and brittle. Most engineering organizations feel this pressure from top to bottom with varying levels of difficulty, since they're all beginning from different starting points.
AI used to sit on top of these systems, but now it's touching the actual plumbing (i.e. the parts that move money, the parts that used to just sit there and work) adding even more opportunity for failure and pressure to create something that holds up.
If you're building during this AI boom, a working agent demo might take you an afternoon. The tricky part is that your competitor can build the same one just as fast. The competitive advantage shows up after the demo, in whether people trust that agent enough to keep using it. If you're an enterprise running decades-old systems, it's a different problem: you can't rebuild from scratch, and you don't have the luxury of waiting. You have to build forward from what you've already got.
Temporal meets both of these teams where they are. Developers write ordinary code, in whatever language the job calls for and whatever tool it needs, and Temporal handles the orchestration across systems for as long as it takes. State gets preserved and work recovers from failures automatically. We call this Durable Execution. It's what lets an application wait days for approval and pick right back up where it left off after an outage, without a developer rebuilding that machinery by hand every time.
We've been at this since before the boom #
Temporal co-founders Samar Abbas and Maxim Fateev were working on this problem long before AI took off, back when software was moving from monoliths into distributed systems. At Amazon, Max led the messaging infrastructure that helped lay the groundwork for SQS, then went on to lead Simple Workflow Service (SWF). Samar joined the team that brought SWF to the public in 2012. At Microsoft, Samar co-created the open-source Durable Task Framework, and Microsoft later built Azure Durable Functions on top of it. The two reunited at Uber to build Cadence, which grew to more than 100 internal use cases in three years before going open source in 2017. They left Uber in 2019 to build Temporal as an independent, open-source platform.
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