Palantir

Liquid AI

Palantir

Palantir's business model is enterprise software — specifically, large multi-year contracts with governments and corporations. Contracts typically start at $1-5 million and can scale to hundreds of millions annually for large government agencies.

The sales process is uniquely intensive. Palantir deploys "forward-deployed engineers" (FDEs) who embed directly with customers for months, configuring the platform for specific use cases.

This hands-on approach is expensive but creates deep integration that makes switching nearly impossible. Once Palantir is embedded in an organization's workflows, it's practically permanent.

Revenue split has shifted over time. Government contracts (US and allied nations) historically dominated, but commercial revenue has been growing faster.

By 2024, commercial revenue approached 45% of total. Annual revenue exceeded $2.8 billion.

The company has been profitable since 2023.

Liquid AI

Liquid AI builds foundation models, the big general-purpose brains that power chatbots and other AI tools. The difference is efficiency.

Their models, called Liquid Foundation Models, are designed to do more with far less memory and computing power. Companies pay to use them, either through a cloud API or by running the models on their own machines.

That second option matters. A bank or a hospital often cannot send private data to someone else's server.

Liquid AI lets them keep the model in-house. The pitch to a customer is basically this.

You get strong AI without renting a mountain of expensive chips.

Palantir

Palantir was born from the aftermath of September 11, 2001. Peter Thiel — PayPal co-founder and contrarian investor — realized that the same fraud-detection algorithms PayPal used to catch financial criminals could help intelligence agencies catch terrorists.

The US government had mountains of data but terrible tools for connecting the dots.

Thiel co-founded Palantir in 2003 with Alex Karp (a Stanford law graduate who then took a PhD in social theory at Goethe University in Frankfurt, studying under Jürgen Habermas), Joe Lonsdale (a Stanford student who'd worked at Clarium Capital), Stephen Cohen (an engineer), and Nathan Gettings (a Clarium colleague). They named it after the palantíri in Tolkien's Lord of the Rings — the seeing stones that let you view distant events.

The CIA's venture arm, In-Q-Tel, was the first investor and first customer simultaneously. The initial product, Palantir Gotham, was built specifically for intelligence analysts who needed to find connections across massive, messy datasets — linking phone records, financial transactions, travel data, and classified intelligence into a single coherent picture.

The company operated in extreme secrecy for its first decade, with most employees unable to discuss what they actually built.

Liquid AI

Liquid AI is a spinout from MIT's Computer Science and Artificial Intelligence Laboratory, better known as CSAIL. The core science came from Ramin Hasani, who spent his PhD studying the nervous system of a tiny worm called C.

elegans. That worm has just 302 neurons and still manages to move, hunt, and react to its world.

Hasani and his collaborators asked a simple question. What if you built an AI that worked more like those neurons and less like a giant static network?

The answer was the liquid neural network, a model whose internal wiring keeps adjusting even after training is done. The team incorporated the company in 2023.

Daniela Rus, who runs CSAIL and is one of the most respected robotics researchers alive, came on as a co-founder. So did Mathias Lechner and Alexander Amini, both longtime research partners of Hasani.

Palantir

Palantir's growth strategy for two decades was simple: get inside the US government, prove indispensable, and expand from there. CIA led to NSA.

NSA led to the Army. The Army led to the Air Force.

Each agency saw what the others were doing and wanted it.

The AIP launch in 2023 was the commercial growth inflection point. By integrating large language models into the platform, Palantir made its data analytics accessible to non-technical users.

A supply chain manager could ask questions in plain English and get answers from their data. This dramatically expanded the potential user base within existing customers and attracted new commercial clients.

"Boot camps" became the commercial go-to-market innovation. Palantir runs intensive multi-day workshops where potential customers bring their actual data and problems, and Palantir engineers build working prototypes on the spot.

Companies leave with tangible proof of value, which accelerates the sales cycle dramatically.

Liquid AI

The growth angle is size, or the lack of it. Most frontier models are so heavy they only run in data centers.

Liquid AI aims for models light enough to run on a phone, a car, or a factory robot. That opens doors the giants cannot easily reach.

The AMD partnership pushes the same idea. AMD makes chips, and it wants efficient models that show off its hardware.

So AMD led the Series A and became both an investor and a distribution partner. Liquid AI also releases open models to researchers, which builds a following before the sales team ever makes a call.

Palantir

The ethical debate follows Palantir everywhere. Privacy advocates have criticized Palantir's work with ICE (Immigration and Customs Enforcement), police departments, and intelligence agencies.

The company has been accused of enabling mass surveillance. Karp has been unapologetic — arguing that democracies need powerful analytical tools and it's better that a company with ethical guidelines builds them than the alternative.

Customer concentration was a historical risk. For years, a handful of massive government contracts drove the majority of revenue.

Losing a single contract could crater a quarter. The push into commercial has diversified the revenue base, but government still represents over 55% of revenue.

Valuation has been the market debate. Palantir trades at astronomical revenue multiples (60-80x revenue at its 2024 peaks), which assumes massive future growth that may or may not materialize.

Bears argue it's the most overvalued stock in tech. Bulls argue that AIP will drive exponential commercial growth.

The debate is loud and ongoing.

Liquid AI

The honest problem is Goliath. OpenAI, Google, Anthropic, and Meta have raised tens of billions of dollars between them.

Liquid AI has raised under $300 million. The transformer architecture those giants use is battle-tested and improving fast.

Liquid AI has to prove its different approach not only works but keeps working as models get bigger. Betting against the most successful design in AI history is bold.

It is also the kind of bet that ends in either a great acquisition or a quiet shutdown, with not much room in between.

Palantir

Palantir Gotham — the original intelligence platform used by government agencies for counterterrorism, military operations, and law enforcement. Integrates and analyzes data from disparate classified and unclassified sources.

Palantir Foundry — the commercial platform that lets corporations build data-driven applications without coding. Used for supply chain optimization, clinical trials, financial modeling, and manufacturing.

Palantir AIP (Artificial Intelligence Platform) — launched in 2023, this layer brings large language models and generative AI into Palantir's existing platforms, letting users query and act on their data using natural language. The product that supercharged the stock price.

Palantir Apollo — a continuous delivery system that manages software deployment across every environment: cloud, on-premise, classified networks, and even air-gapped military systems.

Liquid AI

The main products are the Liquid Foundation Models, a family that ships in several sizes so a customer can pick the smallest one that does the job. The second generation, LFM2, arrived in 2025, including LFM2-VL vision-language models built for phones, laptops, wearables and embedded chips.

The company has leaned hard into on-device AI rather than the cloud. The focus is always the same.

Match the quality of a much larger model while using a fraction of the memory and power.

Palantir

In-Q-Tel (the CIA's venture arm) was the first investor and provided both capital and credibility. Peter Thiel's Founders Fund invested from the founding.

The company raised extensively from institutional investors including Tiger Global, Dragoneer, and Sompo Holdings. The September 2020 direct listing on the NYSE (similar to Spotify — no new shares sold) valued the company at approximately $22 billion.

The stock subsequently surged past a $200 billion market cap in early 2025.

Liquid AI

It started with a $37.5 million two-stage seed in December 2023 at a $303 million valuation, from OSS Capital, PagsGroup, Automattic (the company behind WordPress), Samsung Next and others. Angels included GitHub co-founder Tom Preston-Werner, Shopify's Tobi Lütke and Red Hat co-founder Bob Young.

Then AMD Ventures led the $250 million Series A in December 2024, which is unusual because AMD is a chipmaker, not a typical venture fund. That backing gave Liquid AI both money and a hardware ally.

When a major chip company writes the lead check on an efficiency-focused model maker, it signals a bet that the future of AI is not just bigger, it is leaner.