AI Startup Funding Tracker

Databricks raised over $4 billion in a Series L round led by Insight Partners, Fidelity, and J.P. Morgan Asset Management at a $134 billion valuation, marking a 34 percent increase from its $100 billion valuation just three months earlier in August 2025. The San Francisco-based data intelligence platform crossed $4.8 billion in annual revenue run-rate during Q3 2025, growing 55 percent year-over-year with over $1 billion coming from AI products alone, demonstrating explosive demand for AI infrastructure. The company is investing heavily in three strategic products: Lakebase (the first serverless Postgres database purpose-built for AI), Agent Bricks (platform for building and scaling multi-agent systems), and Databricks Apps (user experience layer for deploying data and AI applications), positioning itself as the foundational infrastructure for enterprises building the next generation of AI agents and data-intelligent applications in the age of vibe coding and generative AI.

Unconventional AI, founded by former Databricks AI head Naveen Rao, raised $475 million in seed capital at a $4.5 billion valuation—one of the largest pre-launch funding rounds in AI history and the first installment toward a goal of up to $1 billion total fundraising. The round was led by Andreessen Horowitz and Lightspeed Ventures, with participation from Lux Capital and DCVC, reflecting extraordinary investor confidence in Rao's vision to create computers "as efficient as biology." The company is developing biology-inspired neuromorphic computing systems designed to be orders of magnitude more energy-efficient than current GPUs by mimicking the human brain's 20-watt efficiency, directly addressing the escalating power demands of AI infrastructure that threaten to outpace available electricity supplies as models and data centers continue to scale exponentially.

Cyera raised $400 million in a Series F round led by Blackstone, valuing the Israeli-founded data security unicorn at $9 billion and positioning it as the second-most valuable private cybersecurity company globally. The investment represents a remarkable 50 percent valuation increase in just six months, following the company's $540 million Series E at $6 billion in June 2025, bringing total funding to approximately $1.7 billion since founding in 2021. Cyera specializes in Data Security Posture Management (DSPM), using AI to automatically discover, classify, and protect sensitive data across multi-cloud, SaaS, and on-premises environments, addressing the critical blind spot as enterprises struggle to track exploding data volumes generated by AI tools. Founded by two Unit 8200 veterans with deep cybersecurity expertise, the company reports 353 percent growth in Fortune 500 customer adoption over 18 months and has expanded to nearly 800 employees across 10 countries, serving major clients including Block, OpenAI, and Fortune 100 banks in the rapidly growing $24 billion global data security market.

Lovable raised $330 million in a Series B round that values the Stockholm-based AI coding startup at $6.6 billion, more than tripling its $1.8 billion valuation from just five months earlier. Co-led by CapitalG (Alphabet's growth fund) and Menlo Ventures, with participation from Nvidia's NVentures, Salesforce Ventures, and multiple other strategic investors, the round reflects explosive growth in the "vibe-coding" market where users build complete applications using only natural language prompts. Founded in 2024, Lovable achieved unprecedented growth metrics by reaching $100 million in annual recurring revenue within eight months of launch, then doubling to surpass $200 million ARR just four months later in November 2025. The platform enables product managers, designers, and non-technical founders to create production-ready applications without writing code, serving enterprises like Deutsche Telekom, Klarna, Uber, and Zendesk while facilitating over 100,000 new projects daily and accumulating 25 million total projects in its first year, with applications built on the platform recording more than 500 million visits in the past six months alone.

Radiant Nuclear raised more than $300 million in a Series D round led by Draper Associates and Boost VC, just six months after its $165 million Series C, bringing total capital to over $500 million as the California-based startup races to commercialize portable 1-megawatt Kaleidos microreactors designed to provide always-on power for AI data centers, military installations, and remote operations. The company was selected by the U.S. Department of Energy to conduct the first test of its reactor design at Idaho National Laboratory's DOME facility in summer 2026, making it the first new U.S. reactor to be tested at this cutting-edge facility and validating technical progress through rigorous government review. Radiant has already secured commercial traction with a deal for 20 reactors from data center giant Equinix and an agreement with the Department of the Air Force, while preparing to break ground on its R-50 factory in Oak Ridge, Tennessee that will eventually produce 50 units annually, positioning the company to deliver operational reactors in the late 2020s if regulatory approvals and testing proceed successfully amid surging demand for reliable power as AI workloads drive unprecedented electricity consumption.

Tebra, a provider of patient record software for healthcare private practices, raised $250 million in combined equity and debt financing to invest in AI and automation capabilities that reduce administrative burden and improve patient outcomes. Hildred Capital Management led the equity financing, which constituted most of the round, while JP Morgan provided debt funding for the Corona del Mar, California-based company. The platform serves private medical practices with comprehensive electronic health records, practice management, and patient engagement tools, positioning itself to integrate AI-powered automation into clinical workflows amid growing demand for healthcare technology that helps physicians focus more time on patient care rather than paperwork. The funding will accelerate development of intelligent features that automate appointment scheduling, billing, insurance verification, and documentation while maintaining HIPAA compliance and data security standards critical to healthcare organizations.

Chai Discovery raised $130 million in a Series B round co-led by Oak HC/FT and General Catalyst, roughly doubling its valuation to $1.3 billion and bringing total funding to approximately $225 million as the San Francisco biotech startup applies large-scale AI foundation models to predict molecular interactions and design novel antibody drugs and biologics. The company uses transformer architectures similar to GPT-4 and Claude but trained specifically on biochemical data to predict protein structures and molecular binding, aiming to compress the typical decade-long, billion-dollar drug discovery timeline to mere months by computationally screening billions of candidates before synthesizing promising molecules for wet lab validation. Chai Discovery released the open-source Chai-1 model demonstrating state-of-the-art performance on protein structure prediction benchmarks, building an ecosystem of researchers using its technology while pursuing internal drug discovery programs that could eventually be licensed to pharmaceutical companies or advanced through clinical trials. With continued investment from OpenAI alongside leading healthcare venture firms, Chai positions itself at the convergence of AI and biology where foundation models trained on molecular data could unlock the same transformative capabilities for drug discovery that language models achieved for text generation.

Mythic raised $125 million in a Series D round led by DCVC to commercialize its analog processing unit (APU) that claims to be 100 times more energy-efficient than current GPUs for AI workloads, addressing one of the biggest challenges facing AI infrastructure today. The Austin-based startup, led by former Nvidia veteran Taner Ozcelik, has developed compute-in-memory technology that integrates memory directly into the chip to reduce power consumption and latency while dramatically improving performance per watt. The company's Starlight platform contains multiple APUs that cumulatively consume less than one watt of power, targeting edge systems such as robots as well as data center deployments where energy efficiency is becoming increasingly critical. Internal benchmarks show Mythic APUs can achieve up to 750 times more tokens per second per watt running trillion-parameter LLMs compared to Nvidia's highest-end GPUs, positioning the company as a serious challenger in the AI hardware market with backing from strategic investors including Honda Motor Co. and Lockheed Martin alongside major venture firms.

Neural Concept raised $100 million in a Series C round led by Growth Equity at Goldman Sachs Alternatives to scale its CAD-native, physics-aware AI platform that accelerates product development for major manufacturers by embedding AI directly into design and simulation workflows. The Lausanne-based startup helps engineering teams at General Motors, GE Vernova, Leonardo Aerospace, Safran, and multiple Formula 1 teams reduce development cycles by up to two years while cutting late-stage redesigns by 30-50 percent, claiming to save customers upwards of $50 million annually. The platform allows teams to explore millions of design options earlier in the process rather than following traditional trial-and-error approaches, transforming engineering into a data-driven workflow where tradeoffs and constraints can be understood and optimized from the start. The company plans to unveil a breakthrough generative CAD capability in early 2026 that will enable AI to generate initial complex 3D geometry from high-level constraints, potentially revolutionizing how advanced systems like future vehicles and spacecraft are designed.

Last Energy raised $100 million in an oversubscribed Series C round led by the Astera Institute, positioning the Austin-based nuclear startup to advance compact 20-megawatt modular reactors specifically designed for AI data centers and energy-intensive industrial operations requiring reliable carbon-free power. The company differentiates by using proven pressurized water reactor technology with low-enriched uranium fuel and off-the-shelf components scaled down through integrated hermetic steel containment, betting that regulatory approval and supply chain maturity favor evolutionary rather than revolutionary reactor designs. Last Energy was selected for the U.S. Department of Energy's Reactor Pilot Program in August 2025, secured a lease at Texas A&M RELLIS Campus, and signed an Other Transaction Agreement with DOE for an anticipated 2026 criticality demonstration, while also completing a Preliminary Design Review in the United Kingdom to pursue international deployment. The funding will accelerate detailed engineering, regulatory submissions in both U.S. and UK markets, business development to convert customer interest into binding contracts, and potentially beginning factory construction to manufacture multiple reactors annually once initial demonstration succeeds.

Ankar raised $20 million in Series A funding led by Atomico with participation from Index Ventures, Norrsken VC, and Daphni, bringing total capital to $24 million as the London-based startup founded by Palantir veterans expands its AI platform modernizing "decades out of date" patent management workflows. The platform analyzes over 150 million patent applications and scientific papers to help patent attorneys and corporate IP teams draft applications more efficiently, identify prior art, track competitor landscapes, and automate administrative tasks that consume disproportionate time in the patent prosecution process. Ankar's AI models are trained specifically on patent corpus data including technical specifications, claim language, and successful prosecution strategies, enabling more accurate outputs than general-purpose AI assistants while integrating directly into existing workflows through Microsoft Word add-ins. The funding will support U.S. market expansion with offices in Silicon Valley, Boston, and Austin, expansion to additional patent office jurisdictions beyond USPTO and EPO, and deeper integrations with enterprise IP management systems, targeting the $50 billion-plus global patent services market where Fortune 500 companies spend hundreds of millions annually on attorney fees and patent operations.

Sequence raised $20 million in Series A funding led by 645 Ventures with participation from Andreessen Horowitz, Firstminute Capital, Passion Capital, Dig Ventures, and Vor Capital, reporting 10x revenue growth as the London and New York-based fintech startup scales its AI-powered platform that automates billing, contract processing, and invoicing workflows for finance teams. The platform uses AI to extract key terms from sales contracts including pricing and payment schedules, automatically generates invoices based on contract terms, routes approvals, matches payments, and provides real-time revenue metrics, positioning itself as the automation layer between sales systems like Salesforce, contract platforms like DocuSign, and financial systems like NetSuite without requiring organizations to replace existing infrastructure. Sequence serves SaaS companies needing subscription billing automation, professional services firms requiring project-based invoicing, and enterprises with complex multi-year contracts, addressing the persistent challenge that revenue recognition and billing remain largely manual at most organizations despite billions invested in ERP and financial automation.

Trigger.dev raised $16 million in Series A funding led by Standard Capital to expand its open-source developer platform for building AI-driven task workflows and autonomous agents that reliably orchestrate complex operations across multiple APIs, databases, and AI models. The platform addresses the fundamental challenge that while large language models excel at individual tasks, building production AI systems that chain together multiple steps, handle failures gracefully, and maintain state across long-running operations remains extraordinarily difficult with existing tools that either lack AI-native capabilities or struggle with production reliability concerns. Trigger.dev provides an open-source TypeScript framework specifically designed for AI workflows, combining reliability engineering patterns from mature orchestration systems like Airflow and Temporal with AI-native capabilities including prompt management, model switching, and handling non-deterministic outputs, while offering both self-hosted deployment and cloud-hosted versions with enterprise features.

Resolve AI achieved unicorn status with a Series A funding round led by Lightspeed Venture Partners that values the incident remediation startup at $1 billion despite being founded less than two years ago by former Splunk executives who previously built and ran Splunk's observability business. The platform automates the traditionally manual process of identifying, diagnosing, and resolving production system failures that site reliability engineers handle through on-call rotations, using AI to continuously monitor systems, correlate alerts to identify root causes, and execute remediation workflows automatically when confident in the diagnosis. Reporting approximately $4 million in current annual recurring revenue, Resolve AI addresses the massive operational challenge as software systems become more complex and distributed across multi-cloud infrastructure, claiming to resolve 60-80 percent of production incidents without human intervention and reducing mean time to resolution from hours to minutes.

Yann LeCun, the Turing Award-winning AI researcher and former Meta Chief AI Scientist, launched fundraising talks that would value his new venture Advanced Machine Intelligence (AMI) Labs at approximately €3.5 billion (~$3.65 billion) before the company has even officially launched operations, seeking to raise €500 million in what would represent one of the largest pre-launch funding rounds in AI history. Less than a month after departing Meta in November 2025, LeCun plans to establish AMI Labs headquarters in Paris with Alexandre LeBrun (founder of health-tech startup Nabla) as CEO, pursuing development of "world models"—AI systems that understand physics, maintain persistent memory, and can plan complex actions rather than simply predicting the next token like current language models. LeCun has been vocal that "Silicon Valley is completely hypnotized by current generative AI models" and believes fundamental breakthroughs require research outside the Bay Area ecosystem, positioning Paris as the hub for alternative AI paradigms that could eventually surpass capabilities of today's large language models through fundamentally different architectures.