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!
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,
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.
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,
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,
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.
Vertical SaaS built the digitization layer for industries, but it always hit a ceiling. Vertical AI now breaks that ceiling.
A new post from @jpsanday@CroomBeatty@samanthasborja@sabrinarlu on what it takes to build something lasting, and a market map of where the next wave
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.
@glproductions@OpenAI It's generally usable now, within Pace! If you work at a carrier, broker, or MGA in P&C or Life Insurance reach out and we can get you started.
Computer Use agents have crossed a major threshold for enterprise reliability.
Over the past few months, we’ve partnered closely with @OpenAI to stress-test their new GPT 5.4 model on the hardest UIs out there: legacy insurance portals.
@pacecom agents navigate dense admin interfaces 1000s of times a day to enter new risk submissions and claims. By collaborating directly with frontier labs, Pace Computer Use can now complete complex tasks on the same software your teams do at human accuracy and superhuman scale 24/7.
"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.
To understand the 4 technical leaps that make Computer Use agents viable in production today, read this breakdown from @jamiecuffex.com/jamiecuffe/sta…
Anthropic just released Sonnet 4.6, their most capable model for computer use. We've been testing it with the @claudeai team ahead of today's launch.
It hit 94% on our Complex Insurance Computer Use Benchmark. Early Claude models scored around 30% on the same tasks.
For the first time, the "mid-sized" Sonnet model has outperformed the heavier Opus 4.6 on our hardest tasks.
Pace agents navigate carrier portals, legacy systems, and dense insurance interfaces thousands of times a day. This requires reasoning through edge cases in environments that weren't built for automation.
We partnered with the @AnthropicAI team to improve performance on exactly these kinds of workflows. We've seen Sonnet 4.6 self-correct through failures in ways previous models couldn't — and we're already shipping it to our customers.
For our insurance partners, this means higher straight-through processing rates and faster turnaround for their policyholders.
Grateful to the team for the partnership and the shoutout in the launch blog post.
This is Claude Sonnet 4.6: our most capable Sonnet model yet.
It’s a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design.
It also features a 1M token context window in beta.
While the market panics over headlines, we’re busy deploying the reality.
The future of insurance isn't about replacing the broker or carrier. It's about giving them superpowers.
We see it in the data every single day.
Nobody buys a seven-figure insurance policy from a chatbot.
This week's $25B selloff in insurance stocks tells you everything about how badly the market misunderstands what Al actually does to this industry.
I work with some of the largest carriers and brokers in the world on
The scaffolding is coming off AI agents. The way we build with AI agents is changing yet again.
@jamiecuffe at @pacecom talks through how to build a vertical software company that accelerates along with every step change in model capability.
With AI, the goal isn’t just to do the same work as humans. AI can handle the rote tasks and free people to apply our judgment wherever it’s needed most.
"How did you pull that off? That's not normal."
That was @gradypb's reaction when @jamiecuffe shared that 100% of our pilots have gone to full production.
In the current AI hype cycle, it's easy to build a demo that dazzles.
It is much harder to build a product that survives real insurance operations: messy data, complex edge cases, and zero tolerance for error.
We don't just ship software. We do the hard work upfront to understand the domain as deeply as the customers we serve.
Jamie joined Pat and @laurenmhreeder on @sequoia's Training Data to discuss what it takes to become the AI operations partner for the world's leading insurers.
Watch the clip below. 👇
Everyone asks: "Can AI really be as accurate as a human?"
The honest answer? It has to be more accurate.
Ops teams hire thousands and hope they all perform like the top 1%. But humans get tired. They have bad days. Quality variance is a feature of the model.
At @pacecom, we solve for that variance. You scale the judgment of your absolute best worker—the one who never misses an edge case—infinite times.
I joined @laurenmhreeder and @gradypb on @sequoia's Training Data podcast to talk about why the next decade of operations isn't just about labor arbitrage. It's about perfect consistency.
@jamiecuffe The future of operations isn't about throwing more bodies at the problem — it's about building systems that never miss. Great discussion with the @Sequoia team.
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