We raised a $120M Series A at a $1B valuation, led by Spark Capital. We are hiring in 40+ roles across mechanical, electrical and software engineering, robotics, power systems, operations and more in the San Francisco Bay Area and Austin. Full article: bloomberg.com/news/articles/…

Announcing the Artificial Analysis Search Index, benchmarking how search API providers perform on quality, cost, and speed when used by an agent. We are initiating coverage with Parallel, Exa, Firecrawl, You (dot) com, Tavily, Keenable, and Brave Search is one of the most important tools for agents. Search providers make different choices about how they search, rank, and package results, and those choices change what the model reads and how it acts. We are expanding our benchmarking coverage to search APIs, so developers can pick a search provider on measured quality, cost, and speed. Each provider result pairs a search API provider with the same model, GPT-5.6 Luna (medium). The model runs inside Stirrup, our open-source agent harness, with tools for searching and fetching pages from the web - only the search provider behind the search tool changes. At launch, the leaderboard covers 11 results across 7 search providers, and we’ll keep expanding coverage as we look to provide the most accurate and comprehensive benchmarking of search providers for AI agent usage. Key elements of the Artificial Analysis Search Index: ➤ Three equally weighted benchmarks: the Search Index is the average of DeepSearchQA (900 broad research questions that need many searches, graded with an F1 score over answer items), BrowseComp (a 200-sample hard subset of facts that need multi-hop browsing), and AA-Omniscience (a 600 question private subset, balanced across 6 domains) ➤ Same agent, different search provider: the agent has 25 turns available to complete each task. Its web search tool returns the search provider's native response payload (with content modes standardized to snippets), with a maximum of 10 results and contamination sources filtered out ➤ Model-only baseline: we compare search agent results to the same model answering single-shot without tools, showing how much each provider lifts the model above its internal knowledge ➤ Cost and Time per Task: we aggregate the time and cost spent on both model inference and search. This is key - search APIs have different cost and latency structures, but these can be offset where they help an agent use fewer turns and save on costly language model inference Key results: ➤ Parallel, Exa, and Firecrawl have the strongest overall performance, with Artificial Analysis Search Index scores of 75, 74, and 73 respectively at launch ➤ All search providers tested substantially improve knowledge-based benchmark performance: the model only baseline scores 33 on the Search Index, while search-included provider results score between 65 and 75 ➤ Focused search results reduce spend on model inference: Parallel Search (advanced) search costs more per task than Parallel Search (basic) but less per task in total ($0.084 vs $0.11). Higher quality results cut the model's token use by over 40% in this case, more than offsetting increased search costs while reaching higher benchmark scores ➤ Fast search calls do not guarantee fast tasks: Parallel Search (turbo) has the fastest average search calls among Parallel's tiers (0.51s per query vs 1.03s for Parallel Search (basic)) but the basic tier scores higher on quality (73 vs 67) and the two land close on total time per task

The startup Lumilens, which develops optical technology for data centers, has raised over $700 million at a $5.5 billion valuation on.wsj.com/3RY8njw

Big day for Convex! First, we raised $57M led by @insightpartners, with participation from @a16z, @sparkcapital, @TheEtnaLabs, and @justinkan. Read more on our blog: news.convex.dev/convex-raise… 🧵

Our biggest round yet: @K2SpaceCo has raised a $500M Series D at a $6.8B post-money valuation. The round was led by @kleinerperkins and @ICONIQCapital, with participation from @CapitalG, @lightspeedvp, @AltimeterCap, @sparkcapital, Sands Capital, @ARKInvest, @TRowePrice, and other existing investors. "Scaling” is probably the word I’ve used most often the past few months in conversations with our investors, customers, and employees when talking about what’s next for K2 Space in 2027 and beyond:  --We’re going to continue to scale up mass production, to deliver against the $1B + in contracts we’ve won to-date. --We’re going to scale up the satellite itself, from the 20kW Mega to the 100kW class Giga. Its no longer just 100kW, but we’ll save that update for another day. The capital from the Series D will turbocharge this scaling.   Thanks to everyone who has been on this journey with us for the last four years – let's keep building bigger.

Today, Cadence is announcing our $100M Series C, led by @SparkCapital, with participation from @ThriveCapital, @generalcatalyst, @coatuemgmt, @BCapitalGroup, Corewell Health Ventures, Memorial Hermann, and Duke Health. Together with the leading health systems in the US, we are automating the treatment of chronic disease, delivering better outcomes to 100,000+ patients. Our clinical AI monitors patients daily, surfaces risk early, coordinates action, and extends clinicians so they can focus on the decisions that require them. The results: - 27% fewer hospital admissions - $1,302 annual cost reduction per patient - $2.7M in Medicare savings every week - 70% relative improvement in blood pressure control - Median alert response time of 3.5 minutes AI is improving clinical care. This round is about scaling world-class care from 100,000 patients to millions. I’m deeply grateful to our patients, partners, investors, and every member of the Cadence team. We’re building the standard for how chronic disease gets treated in America.

! @USDOT and @FAANews have awarded ASI a 12-year $875 Million software and AI contract contract to deploy the Flow Management Data & Services (FMDS) and Strategic Management of Airspace, Routing, and Trajectories (SMART) programs. We’re excited to give the American people the Air Traffic Control system they deserve!

Introducing Athena: the industry coalition to protect open source software from AI attacks. Athena is operational today. More than two dozen members. It's processed 20,000+ findings and generated 2,000+ patches across 500+ open source projects. Join us: chainguard.dev/athena

Today, we are thrilled to officially launch RadixArk with $100M in Seed funding at a $400M valuation. The round was led by @Accel and co-led by @sparkcapital. RadixArk exists to make frontier AI infrastructure open and accessible to everyone. Today, the systems behind the most capable AI models are concentrated in a small number of companies. As a result, most AI teams are forced to rebuild training and inference stacks from scratch, duplicating the same infrastructure work instead of focusing on new models, products, and ideas. RadixArk was founded to change that. We are building an AI platform that makes it easier for teams to train and serve the best models at scale. RadixArk comes from the open-source community. We started with SGLang, where many of us are core developers and maintainers, and expanded our work to Miles for large-scale RL and post-training. We will continue contributing to both projects and working with the community to make them the strongest open-source infrastructure foundations for frontier AI. We would like to thank our long-term partners, contributors, and the broader SGLang community for believing in this mission. We're also grateful to @Accel and @sparkcapital, NVentures (Venture capital arm of @nvidia), Salience Capital, A&E Investment, @HOFCapital, @walden_catalyst, @AMD, LDVP, WTT Fubon Family, @MediaTek, Vocal Ventures, @Sky9Capital and our angel investors @ibab, @LipBuTan1, Hock Tan, @johnschulman2, @soumithchintala, @lilianweng, @oliveur, @Thom_Wolf, @LiamFedus, @robertnishihara, @ericzelikman, @OfficialLoganK, and @multiply_matrix among others. Thanks for the exclusive interview with @MeghanBobrowsky at @WSJ about our vision.

We raised a Series B led by @sequoia at a $2 billion valuation and I’m excited to welcome @andrew__reed to our board. All our existing investors doubled down: @kleinerperkins, @IndexVentures, @khoslaventures, @firstround, @sparkcapital, @AbstractVC, and @terraincap.

We’re excited to announce today that @mastra has raised a $22M Series A led by Spark Capital. This brings our total capital raised to $35M: