A

Applied Compute

Custom AI models and enterprise agents

Overview

Applied Compute creates customized AI capabilities for enterprises by building proprietary AI models and in-house AI agents, a concept they call Specific Intelligence. Its products train on a company’s own data and are fine-tuned for specific workflows, delivered via a vertically integrated platform that includes training infrastructure, an agent platform, and developer tools on a GPU cluster, with engineers embedded inside customer teams to accelerate deployment. The company differentiates itself by focusing on proprietary data, maintaining its own tech stack, and embedding its engineers with customers to deliver deeply integrated solutions that are hard for competitors to copy. Its goal is to give enterprises a competitive edge by deploying production-ready AI agents and models that fit seamlessly into business operations and processes.

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About Applied Compute

Simplify's Rating
Why Applied Compute is rated
B
Rated B on Competitive Edge
Rated A on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsConsultingEnterprise SoftwareAI & Machine Learning

Company Size

11-50

Company Stage

Series C

Total Funding

$510M

Headquarters

San Francisco, CA

Founded

2025

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What believers are saying

  • Applied Compute raised $350 million on November 2, 2026 at $3.25 billion.
  • It reported $100 million annualized revenue run rate less than 18 months after founding.
  • Customer count more than doubled, with Microsoft, DoorDash, Harvey, and Cognition publicly named.

What critics are saying

  • A $3.25 billion valuation on $100 million run rate leaves no room for misses.
  • If Microsoft or DoorDash churn in 2027, the revenue story collapses.
  • OpenAI, Anthropic, and open-source labs can copy AC2 features within months.

What makes Applied Compute unique

  • Applied Compute ships custom models on AC2, keeping customer weights and workflows proprietary.
  • Its November 2, 2026 update says 40% of customers use both training and inference.
  • The team of ex-OpenAI researchers sells embedded execution, not software alone.

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Funding

Total Funding

$510M

Above

Industry Average

Funded Over

3 Rounds

Notable Investors:
Series C funding is usually for startups that are doing well and are looking for more money to fuel major growth, such as acquiring other companies, expanding into global markets, or launching new product lines. Investors typically include larger venture capital firms and private equity.
Series C Funding Comparison
Above Average

Industry standards

$50M
$50M
$62M
$100M
$350M

Benefits

  • Health Insurance
  • Unlimited Paid Time Off
  • Parental Leave
  • Meal Benefits
  • Relocation Assistance
  • Company Equity

Growth & Insights and Company News

6 month growth

13%

1 year growth

20%

2 year growth

20%
Wired & Willing LLC
Nov 4th, 2026
Marvell to buy Lumentum in $115 billion all-stock deal | AI news November 4, 2026.

Marvell to buy Lumentum in $115 billion all-stock deal | AI news November 4, 2026. 5 hours ago Trend Lines · Wednesday, November 4, 2026 Marvell announced on November 2 a $115 billion all-stock deal to acquire Lumentum, according to Reuters, and other chip and component suppliers could pursue similar scale combinations for AI data center connectivity. You should know. Funding rounds. * Applied Compute: On or around November 2-3, 2026, Applied Compute announced a $350 million funding round at a $3.25 billion valuation led by Elad Gil, with participation from Nvidia, Kleiner Perkins, Lux Capital, Blackstone, Shopify Ventures and others, according to the company and SiliconANGLE. The company, founded less than 18 months ago by former OpenAI researchers, reports reaching a $100 million annualized revenue run rate, revenue paced at that level over a full year, serving customers including Microsoft, DoorDash and Harvey, and plans to use proceeds to expand compute capacity. Rapid revenue scaling at a new AI infrastructure provider highlights enterprise demand for custom model training and inference platforms (Applied Compute, SiliconANGLE). * fal: On November 3, 2026, fal announced a $1.3 billion Series F round led by Bessemer Venture Partners at a $16 billion valuation, double its April $8 billion valuation, with participation from Nvidia, Sound Ventures, HOF Capital and T. Rowe Price, according to TechCrunch, Bloomberg and SiliconANGLE. The company hosts and runs image, video and audio AI models, reported surpassing $800 million in annualized revenue earlier in the year, and said proceeds will fund additional compute capacity after summer rate-limiting due to demand. Surging demand for inference services is driving large raises and rapid valuation growth for specialized AI infrastructure providers (TechCrunch, Bloomberg, SiliconANGLE). M&A. * Marvell-Lumentum: On November 2, 2026, Marvell Technology announced a definitive agreement to acquire Lumentum Holdings in an all-stock transaction with an implied enterprise value of $115 billion for Lumentum, according to Reuters and company materials. One of the largest tech acquisitions of the year, the deal signals continued heavy investment in AI connectivity infrastructure components (Reuters, Marvell, SiliconANGLE). Deep Dive: Optical networking deals for AI data centers. What's new. On November 2, 2026, Marvell Technology announced a definitive agreement to acquire Lumentum Holdings in an all-stock transaction. Reuters, Marvell's release and SiliconANGLE report an implied enterprise value of $115 billion for Lumentum, the full deal value including debt, and an equity value of about $102.5 billion. Lumentum shareholders would receive 4.5 Marvell shares per share and about 33% ownership of the combined company. The deal is expected to close in the first half of 2028, subject to approvals. Marvell says the combination expands its addressable market to $550 billion and targets AI data center optical networking demand, the light-based links that move data inside those facilities (Reuters, Marvell, SiliconANGLE). What it points to. Over the next 30 days, track regulatory and shareholder reaction to the Marvell and Lumentum terms, any competing bids or rival optical networking combinations, and whether peer chipmakers signal their own M&A plans around AI networking as investors test the path to a first-half 2028 close and the $550 billion addressable market claim.

Law360
Nov 4th, 2026
Applied Compute hits $3.25B valuation after $350M funding round

Applied Compute, an artificial intelligence company, has reached a $3.25 billion valuation after raising $350 million in its latest funding round. The company announced the news on November 3, 2026. Latham & Watkins LLP advised it on the deal.

Automation Tools AI
Nov 3rd, 2026
Trajectory raises $45 million to make AI model training accessible to nontechnical experts.

Trajectory raises $45 million to make AI model training accessible to nontechnical experts. November 3, 2026 AI models generally do not learn from mistakes unless they are trained again. Companies adapting general-purpose models for fields such as law and finance often rely on specialist research teams or costly consultants to fine-tune them. Trajectory, founded about a year ago by three Stanford classmates with backgrounds at Google DeepMind and Apple, is seeking to automate that work. The 18-person startup has raised $45 million in a Series A led by Sequoia, with participation from Nvidia, Bessemer Venture Partners, and Bain Capital Ventures. The round values the company at $300 million. Trajectory's platform lets businesses connect an open-source AI model to their applications and collect feedback on its performance. The company uses that feedback to retrain the model so it can improve at specialized tasks over time. Co-founder Ronak Malde said the goal is to help models gain the job-specific experience that foundational models lack. Companies including Harvey and Rogo use Trajectory to post-train open-source models for tasks such as reviewing particular types of legal contracts or valuing companies according to specific methodologies. Decagon, Mercor, and Nvidia are also customers. Trajectory is now making its post-training platform publicly available. The startup says its approach keeps people involved in deciding what successful performance looks like. That distinguishes it from fully autonomous self-improvement, which co-founder Michael Elabd says could produce unintended or dangerous results. Trajectory faces competition from Thinking Machines Lab, Applied Compute, and Prime Intellect. Malde points to the team as a key advantage: he previously worked at Google DeepMind and was among researchers hired from Windsurf, while Elabd also worked at DeepMind and co-founder Arjun Karanam worked on generative foundation models at Apple. The company has also recruited talent from OpenAI, Stripe, and Netflix. Karanam said the company's interface is designed to make post-training accessible to customers without technical expertise. Discover the pinnacle of WordPress auto blogging technology with AutomationTools.AI. Harnessing the power of cutting-edge AI algorithms, AutomationTools.AI emerges as the foremost solution for effortlessly curating content from RSS feeds directly to your WordPress platform. Say goodbye to manual content curation and hello to seamless automation, as this innovative tool streamlines the process, saving you time and effort. Stay ahead of the curve in content management and elevate your WordPress website with AutomationTools.AI - the ultimate choice for efficient, dynamic, and hassle-free auto blogging. Learn More

Applied Compute
Nov 2nd, 2026
Applied Compute hits $100M run rate and raises $350M

Less than 18 months after founding Applied Compute, we've grown from zero to $100 million in annualized revenue run rate.

The Information
Aug 10th, 2026
Applied Compute in Talks to Double Valuation to $3 Billion on Open-Source Demand

Applied Compute, a year-old startup that helps companies run and customize open-source models with their own data, is discussing a new funding round that would value it at around $3 billion, more than double its valuation from a round announced four months ago, according to a person with ...

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