$10M led by @sequoia to build the AI operations partner for insurance Tens of thousands of complex transactions completed 1/100th the workforce of traditional BPOs Read the full post from our founder below ⬇️

Insurance workflows demand highly performant computer use. Our team has made major strides in building cost efficient, self improving harnesses. Read more from @aryanjn9 below:

Computer use is one of our most demanding workloads at @pacecom. Our agents drive real browsers and desktop applications through long, multi-step workflows, where every action depends on correctly understanding the screen before it. It's the one place where we usually have to make tradeoffs between model intelligence and speed. When we tested Sonnet 5, it ran through customer workflows quickly without giving up accuracy, landing at the top of our evals. That combination lets us ship faster, more capable agents that deliver real value to our customers.

Bridging the gap between demo and production requires real engineering depth. Multimodal agents in particular require in-depth context management and robust orchestration pipelines in order to keep them reliable over time. In the below post @yeauxgi shares a behind the scenes look of some of the engineering work that goes behind our multimodal agents and how we've been able to reliably stand these up in production over the last few months.

Most insurance work still lives in systems that were never built to talk to anything else: policy admin platforms, claims systems, the mainframe you reach through a green screen. Still, these are the platforms that hold the data the mission-critical work depends on. Computer use removes that limit. If a person can operate a system, a @pacecom agent can too: it sees the screen, reasons about what's on it, and acts. We've pointed it at the trickiest UIs out there - cluttered policy platforms, 40-year-old mainframes, systems behind two-factor logins - and because it reasons over screens instead of following hardcoded clicks, it doesn't break when a field moves. This is the work nobody could automate, till now. See how we build production-grade multi-modal agents here

Writing and servicing policies doesn’t just happen in one channel. Endorsement requests, cancellations, and first notices of loss often get scheduled by phone, confirmed by text, and followed up via email. @pacecom agents work the way the work actually happens, and in the front office, that often means voice. Voice is also one of the hardest channels to get right in production, because live calls are messy. People interrupt, go off-script, give the wrong information, or call back three days later and expect you to pick up where you left off. At the same time, voice is unforgiving on speed. A caller expects an answer in less than a second, and it still has to be right. So we built the infrastructure to make sure our agents hold up against that reality: In Prompt Studio, you design and iterate on agent behavior in a controlled environment, instead of tuning blindly in production. You set up the graders that score the agent on latency, quality, correctness, and tone, and optimize against them. Then in Simulations you run the agent against hundreds of realistic conversations and those same graders measure how it holds up before a single real customer is on the line. This is why top insurers trust Pace’s voice agents to handle over 90% of calls in their contact center fully autonomously. See how we build production-grade voice agents here.

We got to know Jamie as a college intern at Sequoia, and have built maximum conviction in him over the years. Pace is off to the races with exactly the right AI-native solution for the massive insurance industry. We are beyond thrilled to double down on Pace!

The first wave of AI gave workers better tools. The next wave does the work entirely for them. That's what @pacecom is doing in insurance: autonomous agents handling submissions, claims intake, and data entry end to end. Thrilled to continue partnering with Jamie and the Pace team.

We’re on a mission to build certainty in a relentlessly uncertain world. If you run an insurer and share our vision, let’s build the future together.

Today, Pace has raised a $46 million Series B, co-led by @ThriveCapital and @Sequoia, with participation from @emergencecap and @pruvencapital, to help our customers insure more of the world’s risk. @pacecom agents have completed more than 250,000 critical insurance operations, growing 3x every quarter. The world’s leading insurers, like Prudential, WTW and Convex, trust Pace to scale back-office operations. 60% of the world's losses last year went uninsured. Closing this $9 trillion protection gap starts with AI-native operations.

Yesterday, @MenloVentures published their 2026 Market Map featuring the next wave of vertical AI companies across industries. The framing says it well. Vertical SaaS hit a ceiling because it sat alongside the work. Vertical AI sits inside it. Proud to see Pace featured in the Insurance category alongside some great teams. If you're curious what that looks like in practice for carriers and brokers — reach out.

Excited to share that Pace has been named to the 2026 Enterprise Tech 30 list! Wing VC and Newcomer's ET30 is one of the most closely watched signals in enterprise technology, voted on by 90+ leading investors and corporate development leaders to identify the companies defining what comes next. To be recognized alongside companies like @AnthropicAI @databricks @harvey, and @OpenAI makes this especially meaningful. This year's cohort reflects something we've believed from day one: purpose-built AI for specific industries is winning. For us, that industry is insurance. We're building the agentic AI platform that carriers and brokers rely on to automate their most complex operations across the policy and claims lifecycle. A huge thank you to @Wing_VC and @EricNewcomer for the recognition, and to our team for making it happen.

"The next $1T company will be a software company masquerading as a services firm." Spot-on piece from @JulienBek at @sequoia on the shift toward AI-enabled services. At @pacecom, we're seeing this exact transition play out in the insurance industry right now. The legal industry tipped first. AI copilots helped analysts research and chat across massive volumes of documents. The tool made them faster. Insurance is tipping now, but the requirements are fundamentally different. Instead of just chatting over documents, insurance requires AI agents that can actually execute work. Millions of submissions, endorsements, claims, and policy changes need to be processed every single day. The tasks are well-defined. The SOPs already exist. The work is already outsourced. The future of insurance operations isn't about giving teams another software tool to manage. It's about AI stepping in as a reliable operational partner to actually do the work. A copilot sells the tool. An autopilot sells the outcome. At Pace, we're building the autopilot.