Work Here?
Overview
Company Does Not Provide H1B Sponsorship
Fireworks AI provides an AI inference platform that helps organizations run, customize, and deploy machine learning models. It supports deployment, fine-tuning, and inference workflows, with access to open-source models and on-demand deployment options through a subscription model. The platform enables users to configure and optimize models for production environments, manage variants, and scale AI workloads while controlling costs. Unlike some competitors, the emphasis is on end-to-end production-grade inference and fine-tuning across a range of clients, from tech firms to research institutions and enterprises, with tools tailored for rapid deployment and cost efficiency. The long-term goal is to expand the use of AI in production by building compound AI systems, growing the team, and delivering broader platform capabilities that accelerate AI adoption in real-world settings.
About Fireworks AI
Industries
Data & Analytics
Enterprise Software
AI & Machine Learning
Company Size
201-500
Company Stage
Series D
Total Funding
$1.8B
Headquarters
Redwood City, California
Founded
2022
Get referred to Fireworks AI
See people who can refer or advise you
Simplify's Take
What believers are saying
- Fireworks raised $1.505 billion on July 16, 2026, at a $17.5 billion valuation.
- Revenue crossed $1 billion ARR and 40 trillion daily tokens in July 2026.
- August 2026 Microsoft Foundry GA expands distribution into Azure-startups and enterprise buyers.
What critics are saying
- Microsoft, AWS, and Google bundle inference, compressing Fireworks into a replaceable feature.
- Nexus routes only between specific models today; better frontier releases can erase its savings.
- Cursor and other AI-native customers drive growth; one budget shift can hit revenue fast.
What makes Fireworks AI unique
- Fireworks unifies fine-tuning, inference, and routing for open-weight models in one platform.
- July 28, 2026 Nexus routes workloads by difficulty, cutting routine coding costs 3-5x.
- March 11, 2026 Microsoft Foundry made Fireworks first-party for enterprise open-model deployments.
Help us improve and share your feedback! Did you find this helpful?
Funding
Total Funding
$1.8B
Above
Industry Average
Funded Over
5 Rounds
Lightspeed Venture Partners
Index Ventures
BenchmarkIndustry standards
Benefits
Professional Development Budget
Growth & Insights and Company News
6 month growth
↓ -8%1 year growth
↓ -8%2 year growth
↓ -2%Fireworks AI releases Fireworks Nexus: A drop-in routing and cost-control layer that moves routine coding work to open-weight models. July 28, 2026 Fireworks AI has released Fireworks Nexus, an AI management and routing platform aimed at engineering organizations. It connects the coding tools developers already use to a managed layer of open-weight models. The problem it targets is well documented. Forbes reported that Uber exhausted its entire 2026 AI budget in four months. Claude Code had reached roughly 5,000 engineers after a December rollout. Fireworks cites the same report, noting agentic adoption climbed from about a third of engineers to more than four-fifths in two months. Fireworks frames the underlying issue as a mismatch, not an overspend. Most organizations run routine work at frontier prices. Operational complexity has made switching to open-weight models unattractive for platform teams. Fireworks Nexus. Nexus is composed of three components: 1. Enterprise controls and cost observability: Teams set budgets at the team or company level. They track ROI across models and tools, and enforce policy from one place. Requests run on the Fireworks production inference platform, with US-hosted endpoints, zero data retention, and coverage across 20 global data centers. 2. Workflow continuity: FireConnect is a one-line install that maps harness model slots to Fireworks models. It is released under Apache 2.0 and can be installed from the Fireworks Dashboard in a single command. Claude Code, Codex and OpenCode keep working unchanged. FireConnect runs on Fireworks Serverless APIs that are Anthropic- and OpenAI-compatible, so most tools connect with a base URL and a model ID. 3. Intelligent traffic management: A custom trained model scores each request's difficulty. Routine requests go to a cost-effective open-weight model served by Fireworks. Difficult requests pass through to your existing provider on your own key, which Fireworks states is never stored server-side. The research team reports this typically delivers a 3-5x cost reduction. One important note for anyone planning a rollout. The router is a research preview. It currently routes between Claude Opus 5 and GLM-5.2, so the pass-through path requires an Anthropic key. An all-open configuration routes between Kimi K3 and GLM-5.2 instead. Performance. Fireworks research team has been testing Nexus with dev teams including Notion and Doximity. Preliminary results show a one-third reduction in cost per merged pull request. The research team also reports a blended token rate roughly a quarter of the closed model labs. These are vendor figures from a preview program, and should be read that way. The more useful evidence comes from two independent evaluations Fireworks cites. Faros AI ran 211 real engineering tasks drawn from 12 repositories across seven model-and-harness routes. Claude Code on GLM-5.2 scored 0.568 on a model-based rubric judge. Claude Code on Opus 4.8 scored 0.521. The cost gap was larger than the quality gap: $0.92 per task against $1.76. Cache share was 89.7% and 99.7% respectively, so caching does not explain the result. Faros stresses that the cohort is company-specific and not a universal leaderboard. Arize, in a joint study with Fireworks, evaluated 10 models on 40 Terminal-Bench tasks at six trials each. That is 2,400 runs and $626 of API spend, graded by each task's own test suite. The headline metric is cost per successful task, which counts every failed and retried attempt. Two findings from that study bear directly on the Nexus design. On easy tasks the frontier premium buys nothing: Kimi K2.6 passed 73% where GPT-5.5 passed 69%. On hard tasks only the top tier competes, with GPT-5.5 at 51% and Kimi K3 at 32%. Arize's evaluation harness is open source, so teams can rerun it on their own workloads. Routing simulated over those runs beat every single-model strategy. A deliberate escalation ladder reached $0.525 per successful task while reliably solving 32.3 of 40 tasks. GPT-5.5 alone cost $0.636 and reliably solved 25 of 40. Naive escalation through all ten models cost $1.319, worse than any single model tested. Ladder design is not optional. How teams actually turn it on. There are three practical paths, and they have different blast radii. The FireConnect path is the lowest friction. The installer requires the Claude Code CLI already on PATH, prompts once for a Fireworks API key, registers a plugin marketplace, and writes Claude Code settings with a timestamped backup. It exposes /fireconnect:on, /fireconnect:off, /fireconnect:setup, /fireconnect:models and /fireconnect:set-models. The second path skips the plugin entirely. Set ANTHROPIC_BASE_URL and a Fireworks key, or use the OpenAI-compatible client with a changed base URL and model ID. Arize noted that adding a model to its harness was one config line. That interchangeability is what makes an escalation ladder buildable. The third path is the router itself, which sits in front of an existing frontier contract. Key takeaways. * Independent runs from Faros AI (211 tasks) and Arize (2,400 runs) support routing by difficulty, not by brand. * Fireworks Nexus is a drop-in AI management and routing layer for engineering orgs, announced July 26, 2026. * Three parts ship: enterprise cost controls, FireConnect for workflow continuity, and a difficulty-aware router. * FireConnect is Apache 2.0, installs in one line, and keeps Claude Code, Codex and OpenCode unchanged. * Fireworks quotes 3-5x cost reduction and a 33% drop in cost per merged PR in preliminary customer testing.
Why Prysm Capital, LLC invested in Fireworks: powering the production era of Enterprise AI. July 21, 2026 Nobody at a board meeting asks 'should we use AI?' anymore. Now they ask why the pilot that wowed everyone in March still isn't in production in October, and why the serving bill tripled. Most of the industry has spent the past three years obsessed with building AI models. But a model creates no value until it runs. Every AI application that graduates from demo to production becomes an inference workload, and those workloads are compounding fast. The bottleneck has shifted from model creation to the complex, six-month slog required to reliably serve traffic at a cost acceptable to the CFO. AI spend will represent $1.3 trillion by 2029, growing ~32% year-over-year from 2025-2029, driven largely by agentic AI adoption. As of 2025, 88% of enterprises had reported using AI in at least one business function, up from 55% two years prior. And the open-source model ecosystem, GLM, Moonshot, Qwen, DeepSeek, and others, now trails the closed frontier by as little as a few months, giving enterprises real optionality for the first time. However, actually running these models at scale in production remains the single hardest problem in enterprise AI, largely because meeting the business's demands for latency and reliability requires navigating a complex landscape of constrained GPU compute and enormous serving complexity. It is a hurdle that most teams simply are not equipped to clear on their own, especially as they often lack the rare ML systems expertise needed to solve these infrastructure challenges internally. Fireworks: The Inference Engine for Enterprise AI Prysm Capital, LLC tracked Fireworks for more than a year before its portfolio company Replit, introduced Prysm Capital, LLC to the team. In its first meeting, Lin made it clear they are building frontier training and inference on one platform. Fireworks has built a leading inference platform for enterprises serving and fine-tuning open-weight models in production. On the inference side, Fireworks provides significant cost and performance advantages, delivering roughly 10x better price-per-token economics and up to 5x faster speeds than closed-source alternatives on coding and agentic workloads. Importantly, its capabilities extend beyond inference to custom fine-tuning and reinforcement learning, enabling enterprises to leverage their proprietary data, workflows, context, and more, to better build, serve, and scale models tailored to their specific business needs. Its platform abstracts the complexity of more than 100,000 deployment configuration combinations into one full-stack inference platform spanning post-training, fine-tuning, reinforcement learning, and model serving, providing the tools enterprises need to scale customized models with greater speed and with differentiated economics. Fireworks serves leading enterprise and AI-native customers, including Cursor, Perplexity, Cognition, and Genspark. Annualized revenue run-rate surpassed $1 billion, up from $280 million at its last funding round. Fireworks now processes more than 40 trillion tokens per day, having nearly tripled the daily volume of tokens served on its platform in the same period. That's why Prysm Capital, LLC is proud to participate in Fireworks' $1.5 billion Series D, led by Atreides Management, Index Ventures, and TCV, along with participation from existing investors including Evantic, Lightspeed Venture Partners, and NVIDIA. Its Thesis: Inference and beyond Prysm Capital, LLC always ask: how is this going to be deployed in the real world? Models will keep leapfrogging each other, but Prysm Capital, LLC is prioritizing the essential plumbing that turns AI into a practical business reality. Prysm Capital, LLC started mapping the inference layer eighteen months ago, when Prysm Capital, LLC noticed its portfolio companies' biggest line item was oftentimes serving costs. A coding assistant lives or dies on completion latency. A real-time answer engine can't wait on a slow model. An agent running thousands of steps unravels when the cost-per-token becomes unsustainable. And the pattern is extending beyond AI-natives. Specialized AI is becoming the enterprise default. More companies are moving beyond one-size-fits-all AI and building their own customized models. Fireworks is helping lead that shift. Enterprises are using Fireworks to fine-tune open models on their private data and unique context, creating specialized intelligence for application-specific models that match or outperform generic frontier alternatives on their workloads, while running faster and at a fraction of the cost. 95% of tokens served through Fireworks today are from models that have been specialized. This is the ground on which Fireworks keeps winning enterprise deployments: performance, reliability, and economics that hold up at scale. The Team and the Path Ahead Lin Qiao and her six co-founders have spent their careers on exactly this problem. Qiao and several co-founders were key leaders and engineers behind PyTorch, the open-source framework underpinning much of modern AI. The broader team built and led AI / ML platforms and large-scale production infrastructure across Meta and Google. Few teams have built and operated production ML systems at that scale, and fewer still have turned that experience into a platform others can use. That pedigree shows up in the product. Inference is a crowded, fast-moving market, but Fireworks competes on more than just inference - its advantages compound: custom kernel optimizations that create performance advantages, GPU utilization gains that grow with volume, and a full-stack platform that goes well beyond reselling compute. This platform breadth positions Fireworks as a core layer in an enterprise's AI stack, providing the infrastructure to power tailored solutions at scale across the business. As AI moves from experimentation into production, Fireworks offers exactly what that shift demands: customized open models served with frontier performance, reliability, and economics. Excited to see what comes next as the company invests this new funding into scaling its platform, expanding global infrastructure, deepening its partnerships, and helping more enterprises build specialized intelligence. Disclaimer: For informational purposes only. Not an offer of any securities or of the investment advisory services of Prysm Capital, L.P. References in this piece are provided solely for illustrative purposes to highlight aspects of Prysm Capital's investment approach and do not purport to represent all investments made by Prysm Capital. Past performance is not indicative of future results. May 4, 2026
Top funding rounds week of july 13th. Fundable analyze this past week's biggest raises, including the $1.5B Fireworks AI round and Neko Health's Series C, highlighting a clear surge in Physical AI deals. * 01 Fireworks AI Artificial Intelligence (AI) - Data and Analytics - California $1.5BSeries D Fireworks AI, the specialized intelligence platform, raised a $1.505 billion Series D at a $17.5 billion valuation led by Atreides Management, Index Ventures, and TCV, with participation from Evantic, Lightspeed Venture Partners, NVIDIA, 20VC, Bessemer Venture Partners, Insight Partners, Lone Pine Capital, Menlo Ventures, Operator Collective, Ontario Teachers' Pension Plan, Original Capital, Prysm Capital, Quantum Capital, and TIME Ventures * 02 Zepto Administrative Services - Apps - Maharashtra $801MEquity Zepto, a quick-commerce startup, is raising an $800 million pre-IPO round at a $5.1 billion post-money valuation with anchor participation from Norges Bank Investment Management and Motilal Oswal. * 03 VoltaGrid Energy - Messaging and Telecommunications - Texas $775MEquity VoltaGrid, a US-based power generation company, secured $1.0B in strategic equity comprising a $775M primary raise and a $225M secondary purchase from funds managed by Blackstone Tactical Opportunities and Halliburton Company. * 04 Neko Health Artificial Intelligence (AI) - Data and Analytics - Stockholms Lan $700MSeries C Neko Health, a Stockholm-based HealthTech company, raised €612.7 million ($700 million) in a Series C led by Lightspeed Venture Partners and co-led by O.G. Venture Partners with participation from Atomico, General Catalyst, Lakestar, Liberty City Ventures, Positive Sum, and BDT & MSD, alongside numerous individual backers including Maria Sharapova, Mark Zuckerberg and Priscilla Chan. * 05 Wonder Commerce and Shopping - Food and Beverage - New York $650MSeries D Wonder, a food technology platform, raised $650 million in a Series D at a $9 billion pre-money valuation with participation from existing investors including Accel, GV and NEA and new investors including funds managed by AllianceBernstein, ARK Invest and Kayne Anderson Rudnick Investment Management. * 06 PixVerse Artificial Intelligence (AI) - Media and Entertainment - Central Region $439MSeries C Extension PixVerse, a Singapore-based video-generation startup, raised $439 million in a Series C extension at a valuation north of $2 billion, following an initial Series C led by CDH Investments and with participation from Alibaba, Lollapalooza Capital, Ivy Capital, Grand Mount Capital, Eastern Bell Capital, Mirae Asset, BlueFocus, CloudAlpha, iGlobe Partners, and OCBC's Lion X Ventures. * 07 Crypto.com Blockchain and Cryptocurrency - Financial Services - Central Region $400MEquity Crypto.com, a cryptocurrency exchange, raised a $400 million strategic investment in its first institutional funding round at a $20 billion valuation from Citadel Securities. * 08 Bybit Blockchain and Cryptocurrency - Financial Services - Central Region $400MEquity Bybit, a cryptocurrency exchange, raised a $400M strategic investment from Citadel Securities at a $20B valuation. * 09 Judy Rx Health Care - New York $400MEquity Judi Rx, the pharmacy benefit manager rebranded from Capital Rx, raised a $400M financing round * 10 Chai Discovery Artificial Intelligence (AI) - Biotechnology - California $400MSeries C Chai Discovery, an AI-driven molecular design company, raised $400M in a Series C at a $3.8B valuation led by Index Ventures alongside Kleiner Perkins, Sequoia Capital and Dimension. * 11 AdvanCell Biotechnology - Health Care - New South Wales $315MEquity AdvanCell, a startup developing targeted alpha therapies for prostate cancer, raised $315 million in a funding round. * 12 Walden Robotics Artificial Intelligence (AI) - Data and Analytics - Massachusetts $300MSeed Walden Robotics, a full-stack Physical AI company building and deploying general-purpose robots, raised $300 million in a seed round at a $1.1 billion valuation co-led by Toyota and Deviation Capital with participation from NVIDIA, Boeing, AE Ventures, Samsung Ventures, Prologis Ventures, CoreWeave Ventures, Calibrate Ventures, Colle Capital, Shine Capital, NextView Ventures, Squarepoint Capital, One Madison Group, KAS Venture Partners, Menlo Ventures, and others. * 13 BrainCo Biotechnology - Consumer Electronics - Massachusetts $294.6MEquity BrainCo, Chinese neurotechnology company focused on noninvasive brain-computer interfaces and prosthetics, raised about ¥2 billion (approximately $280 million) in a financing round co-led by IDG Capital and Walden International * 14 Udaan Commerce and Shopping - Other - Karnataka $160MEquity Udaan, an Indian B2B ecommerce platform, raised $160 million in a financing combining fresh equity, additional debt, and convertible bond conversions with participation from Lightspeed Venture Partners and M&G Investments. * 15 Humanoid Artificial Intelligence (AI) - Data and Analytics - England $150MSeries A British robotics startup Humanoid, developing humanoid robots, raised $150M in the first tranche of a Series A at a $1.2B pre-money valuation. * 16 Alpaca Blockchain and Cryptocurrency - Financial Services - Tokyo $135MSeries E Alpaca, a U.S. Investment-as-a-Service platform, raised $135 million in a Series E led by Peak XV (formerly Sequoia India). * 17 Gauntlet Blockchain and Cryptocurrency - Financial Services - New York $125MSeries C Gauntlet, a digital asset risk and optimization firm, raised $125 million in a Series C led by SBI Holdings USA. * 18 BRINC Drones Artificial Intelligence (AI) - Consumer Electronics - Washington $125MEquity BRINC, a public safety drone technology company, raised $125 million in a financing round led by Motorola Solutions with participation from Index Ventures and Dylan Field. * 19 Lumin Digital Financial Services - Software - California $115MEquity Lumin Digital, the compounding growth platform for banks and credit unions, raised $115 million in new capital including a $45 million growth equity tranche at a $1.6 billion valuation led by Light Street Capital with participation from client investors. * 20 Holiday Robotics - 홀리데이로보틱스 Artificial Intelligence (AI) - Data and Analytics - Seoul-t'ukpyolsi $103.5MSeries A Holiday Robotics, a humanoid robot startup/physical AI company, raised 155 billion won in a Series A with participation from existing investors Stonebridge Ventures, Atinum Investment, Intervest, Springcamp and new investors including IMM Investment, SL Investment, KB Investment, Bon Angels Venture Partners, Premier Partners, Almus Investment, SJ Investment Partners, Dasung Ventures, Atinum Capital Partners, Goodwater Capital, the Korea Development Bank, and the Industrial Bank of Korea
This week: Fireworks, Emergent, Glacis Labs, Binance, GENIUS Act. This week overview (July 13 - July 17, 2026): - Fireworks AI closed a $1.505 billion Series D at a $17.5 billion valuation, led by Atreides Management, Index Ventures and TCV with NVIDIA participating, its ARR just crossed $1 billion. - Emergent, an Indian AI-coding startup barely a year old, raised a $130 million Series C led by Creaegis, becoming a unicorn at a $1.5 billion valuation (5x jump in six months). - Glacis Labs raised a $6.8 million seed for ZeroDelta, its multichain crypto clearinghouse, backed by Franklin Templeton and Coinbase Ventures alongside Lightspeed Faction. - Binance launched U.S. equities trading and previewed bStocks, tokenized U.S. stocks designed for 24/7 settlement and DeFi composability. - The GENIUS Act's one-year rulemaking deadline lands July 18: six federal agencies racing to finalize the rules that will govern every stablecoin issuer in the country. Fireworks raises $1.505B, crosses $1B ARR, and the round says the quiet part out loud. Fireworks AI closed a $1.505 billion Series D on July 16 at a $17.5 billion valuation, led by Atreides Management, Index Ventures and TCV, with Lightspeed Venture Partners, Evantic Capital and NVIDIA also participating. The company says it now serves more than 40 trillion tokens a day, with over 95% of that volume coming from models fine-tuned on customers' own proprietary data rather than generic frontier models pulled off the shelf. Fireworks selling the infrastructure layer that lets enterprises take an open-source model, specialize it on their own workflows, and run it in production at scale, with more than 200 models supported across text, image and multimodal formats. The round pushes Fireworks past $1 billion in annualized revenue run rate, a threshold vanishingly few infrastructure startups clear this fast. "There are two paths forward for AI. In one, intelligence belongs to a few big labs, and everyone else rents it. In the other, every company in the world builds specialized intelligence of its own, shaped by the domain only it understands. We are building towards the second," said Lin Qiao, co-founder and CEO of Fireworks. An Indian ai-coding startup went from launch to unicorn in 13 months - What does that even mean anymore? Emergent, the Bengaluru-based AI coding platform founded by brothers Ravi and Madhav Jha, raised a $130 million Series C led by private equity firm Creaegis on July 15, taking its post-money valuation to $1.5 billion, five times its valuation just six months earlier. New investors MNI Ventures-Claypond and Sentinel Global joined existing backers Khosla Ventures, SoftBank's Vision Fund 2, Lightspeed and Y Combinator. Total funding to date: $230 million, raised in barely a year since launch. The numbers behind the markup are real: Emergent's annual run-rate revenue hit $120 million, up 70% in four months, across more than 200,000 paying customers, trucking companies, factories, construction firms and property managers building their own internal software with AI agents instead of hiring developers. When AI-native revenue compounds this fast, growth-stage investors aren't pricing the business as it exists today; they're pricing the fear of missing the last entry point before the company becomes un-investable at any price. That's a rational response to genuinely explosive unit economics. It's also exactly the dynamic that inflated, and then deflated, prior venture cycles, the difference this time is whether $120 million of real, diversified enterprise revenue is enough ballast to keep the multiple honest. Franklin Templeton just backed a crypto clearinghouse. Glacis Labs announced a $6.8 million seed round on July 15 for ZeroDelta, its clearing layer for digital assets, led by Lightspeed Faction with participation from Franklin Templeton, Coinbase Ventures, Again (formerly IDC Ventures), Protein Capital and Techni Ventures. ZeroDelta is a multichain clearinghouse that nets and settles digital-asset flows non-custodially across more than 40 chains - instead of routing every transfer individually on-chain, it matches opposing flows internally so only the net remainder ever touches a blockchain. The platform has already settled over $1 billion in volume and runs at a $1.5 billion annualized rate. Six-figure-to-low-seven-figure seed rounds rarely make a weekly roundup on dollar amount alone. This one matters for the cap table: Franklin Templeton, a 78-year-old, nearly $1.6 trillion asset manager, is now a seed-stage backer of crypto settlement infrastructure, not a later-stage validator writing a check after the category is already de-risked. That's a materially different signal than a crypto-native fund backing the same round. Binance wants to sell you apple stock - on-chain, 24/7. Is that crypto, or is that just finance now? Binance launched U.S. equities trading through its ADGM-licensed broker-dealer, Nest Trading Limited, giving eligible users commission-free access to more than 7,000 U.S.-listed stocks and ETFs with fractional shares starting at $5. Alongside it, Binance previewed bStocks - tokenized versions of select U.S. equities designed to map share ownership on-chain, enabling 24/7 settlement, fractional ownership and DeFi composability, pending FSRA regulatory approval. Binance isn't the first exchange to chase tokenized equities, but the packaging is the story: a crypto exchange built to trade Bitcoin is now positioning itself as a multi-asset financial super app, with regulated equities as the entry wedge and tokenization as the eventual product. That sequencing matters - launch the boring, compliant version first (real shares, real clearing broker, real dividends), then layer the on-chain wrapper on top once the regulatory path is proven. Tokenized stocks keep showing up as "the next big crypto use case" every 18 months, and keep failing to break out of pilot-stage volume, the pattern this cycle might be different only because it's arriving through a KYC'd, broker-dealer front door instead of an anonymous DeFi protocol. Whether bStocks clears real volume once it launches, or joins the long list of tokenized-equity products nobody actually trades, is the open question, but the fact that Binance is willing to build the compliant on-ramp first says something about where the exchange thinks regulatory winds are blowing in 2026. The GENIUS Act's deadline is Friday. Is anyone actually ready? July 18, 2026 marks the one-year anniversary of the GENIUS Act's signing - and the statutory deadline for six federal agencies (the OCC, FDIC, NCUA, Treasury, FinCEN and OFAC) to finalize the rules governing every payment stablecoin issuer in the country. As of mid-July, all public comment periods had closed, but the agencies were still in simultaneous final-rule drafting with days to spare, and the Federal Reserve, also a primary stablecoin regulator under the statute - had not yet issued its own proposed rule, adding pressure to an already tight window. It's worth separating what actually happens Friday from what doesn't: July 18, 2026 is the rulemaking deadline, not an enforcement cliff, the date non-compliant stablecoins actually lose exchange access under the Act doesn't arrive until July 18, 2028. Nobody gets shut off this week. What does happen is that the regulatory scaffolding issuers like Circle and Tether will build their compliance programs around for the next two years finally gets fixed in place, after a year of six-agency negotiation. A missed or rushed deadline here is a bigger crypto story than any single funding round this week, because it resets the clock every stablecoin issuer, exchange and crypto-native VC has been quietly pricing into their 2028 roadmap. Rules finalized on time and coherently across six agencies is a green light for exactly the kind of institutional stablecoin infrastructure bets, like Glacis Labs' clearinghouse, or Binance's regulated on-ramp, that dominated the rest of this week's news.
Fireworks raises $1.505B Series D. Fireworks raises $1.505B in Series D funding led by Atreides Management, Index Ventures, and TCV to scale its specialized AI intelligence platform. Updated July 17, 2026 Fireworks raises $1.505B Series D at $17.5B valuation. Fireworks, based in San Mateo, California, is a specialized intelligence platform that enables enterprises to train and serve custom AI models. The company announced it has raised $1.505 billion in a Series D funding round at a $17.5 billion valuation. Investors. The round was co-led by Atreides Management, Index Ventures, and TCV. Additional investors participating in the round include 20VC, Bessemer Venture Partners, Evantic Capital, Insight Partners, Lone Pine Capital, Lightspeed Venture Partners, Menlo Ventures, NVIDIA, Operator Collective, Ontario Teachers Pension Plan, Original Capital, Prysm Capital, Quantum Capital, and TIME Ventures. Fireworks use of funds. Fireworks plans to use the fresh capital to expand its engineering team and increase its global compute capacity to support rising enterprise demand. The company also intends to deepen its strategic partnerships with cloud providers such as Microsoft and NVIDIA. About Fireworks. Founded with a focus on specialized intelligence, Fireworks provides the infrastructure for companies to customize, serve, and scale open AI models using their own proprietary data, workflows, and customer context. Their platform supports over 200 models across text, image, and multimodal formats, serving enterprise clients such as Uber, Shopify, Doximity, and Revolut. Funding details. Company: Fireworks Raised: $1.505B Round: Series D Funding Date: July 2026 Lead Investor: Atreides Management, Index Ventures, TCV Additional Investors: 20VC, Bessemer Venture Partners, Evantic Capital, Insight Partners, Lone Pine Capital, Lightspeed Venture Partners, Menlo Ventures, NVIDIA, Operator Collective, Ontario Teachers' Pension Plan, Original Capital, Prysm Capital, Quantum Capital, TIME Ventures Software Category: Artificial Intelligence Source: https://www.marketwatch.com/story/nvidia-backed-fireworks-raises-1-5-billion-in-series-d-75df5ad9 Updated July 17, 2026
There are no jobs for Fireworks AI right now.
Find jobs on Simplify and start your career today
About Fireworks AI
Industries
Data & Analytics
Enterprise Software
AI & Machine Learning
Company Size
201-500
Company Stage
Series D
Total Funding
$1.8B
Headquarters
Redwood City, California
Founded
2022
There are no jobs for Fireworks AI right now.
Find jobs on Simplify and start your career today