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The Next Palantir Is Already Being Built, You Just Can’t Buy It Yet: 3 AI Companies to Watch in 2026

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While Palantir Technologies (PLTR) trades near all-time highs at premium multiples, a new generation of enterprise AI platforms is scaling rapidly, and may offer investors a more attractive entry point into the same trillion-dollar opportunity.

Palantir just delivered what many investors viewed as one of the strongest recent earnings reports in enterprise software. In Q4 2025, the company posted 70% year-over-year revenue growth, with U.S. commercial revenue surging 137% and total contract value reaching approximately $4.3 billion. Management issued full-year 2026 guidance of roughly 61% revenue growth, implying about $7.2 billion in revenue. CEO Alex Karp described the company as “an n of 1.”

He may be right. But the market has priced in that story aggressively.

At current prices near $152 per share, Palantir trades at approximately 45x forward revenue based on 2026 guidance, and roughly 73x trailing 2025 revenue, a multiple that leaves limited margin for error and demands sustained execution across multiple years.
For investors who missed the Palantir trade, or who want more favorable risk-adjusted exposure to enterprise AI, the question becomes: which companies are building the next Palantir?

We identified three private companies combining Palantir-like ambitions with valuations that may not yet fully reflect their long-term potential. None is publicly traded today, but each represents a distinct bet on who will control enterprise AI infrastructure over the next decade.

WHAT MAKES A “NEXT PALANTIR”?

Palantir’s moat rests on three pillars: deeply embedded enterprise software that is difficult to replace, a government and defense franchise with high barriers to entry, and an AI platform that transforms data into operational decision-making. The companies below attack different parts of this equation. None is a direct replica of Palantir, but each is building a durable, high-margin position within the same enterprise AI ecosystem.

“The question for investors is not whether enterprise AI is real, it is. The question is whether Palantir at current multiples is the most efficient way to own that trend.”

#1 DATABRICKS Pre-IPO | Valuation: Reported estimates exceeding $100B

Founded in 2013 by the original creators of Apache Spark at UC Berkeley, Databricks built the data lakehouse category from scratch and now provides core data and AI infrastructure for a significant portion of large enterprises, including a majority of the Fortune 500.

Annualized Revenue: Reported at over $5B | YoY Growth: Reported at 65%+ | Subscription Gross Margin: Reported above 80%

Databricks is arguably the most compelling pre-IPO AI infrastructure story of 2026. The company has surpassed a $5 billion annualized revenue run rate while maintaining strong growth, high subscription gross margins, and positive free cash flow. By comparison, Palantir grew 56% in 2025 and is guiding approximately 61% growth in 2026. Databricks is operating at comparable or faster growth rates, at a larger private-market scale, and has not yet entered public markets.

The company recently raised a significant funding round with participation from major institutional investors including Microsoft, BlackRock, Blackstone, JPMorgan, Goldman Sachs, and the Qatar Investment Authority. Reported valuations exceed $100 billion, with some estimates placing it above $130 billion. CEO Ali Ghodsi has stated that an IPO in 2026 is not ruled out, though no filing has been made as of March 2026.

The Palantir comparison: Palantir sits at the decision layer, helping organizations act on data. Databricks sits beneath it, owning the data layer itself. With over 20,000 customers and rapidly expanding AI-driven revenue, the company is positioning itself as foundational infrastructure for enterprise AI. Its continued expansion into databases and AI-native tooling puts it in more direct competition with legacy platforms like Oracle and SAP.

Bull Case: Growth rates comparable to or exceeding Palantir, at a significantly lower implied multiple. A public listing could reprice the entire enterprise AI infrastructure category.

Key Risks: Pre-IPO access is limited to accredited investors. Competition from Snowflake, Google BigQuery, and AWS remains intense. Leadership changes, including the departure of key AI executives, introduce some uncertainty heading into a potential IPO year.

Bottom Line: Public market investors can gain indirect exposure through Microsoft (MSFT), which participated in the latest funding round. Databricks is widely viewed as one of the most anticipated IPO candidates in enterprise software.

#2 GLEAN Private | Series F | Valuation: Industry estimates suggest approximately $7B+

Founded in 2019 by Arvind Jain, a former Google Distinguished Engineer and co-founder of Rubrik, Glean addresses a persistent enterprise problem: employees spend significant time searching for information that already exists internally. Glean connects data across enterprise applications into a unified, permissions-aware knowledge layer, allowing employees to query company information using natural language.

ARR: Reportedly surpassed $200M | Growth: Approximately doubled within the past year

Glean has stated it crossed $200 million in annual recurring revenue in early 2026, roughly nine months after reaching $100 million. A recent funding round reportedly led by Wellington Management at a valuation estimated above $7 billion drew participation from Sequoia, Kleiner Perkins, and General Catalyst. The company has been recognized by industry analysts for innovation in agentic AI and cited by Bloomberg among notable AI startups to watch in 2026.

Read More: 15 AI Stocks That Are Quietly Making Investors Rich

Read More: Undervalued AI Stock Poised For Massive Gains: 10000% Upside Potential

The Palantir comparison: Palantir focuses on high-level operational decision-making, typically within government and large enterprise. Glean targets a broader layer, every knowledge worker within an organization, embedding intelligence into everyday workflows across industries. The total addressable market may be larger and the deployment friction is considerably lower.

Glean’s customer base has expanded beyond technology into finance, retail, manufacturing, and healthcare, sectors that map closely to the professional demographics of this readership.
Bull Case: Approximately 2x revenue growth within a year places Glean among the faster-growing enterprise SaaS companies at this stage. Its architecture, built around permissions, compliance, and enterprise data integration, aligns well with the shift toward agentic AI systems.

Key Risks: Microsoft 365 Copilot, Amazon Q, and Google Agentspace are targeting the same use cases with bundled pricing and the significant advantage of existing enterprise relationships. Middleware businesses have historically faced margin pressure when hyperscalers move into adjacent markets.

Bottom Line: At an estimated valuation above $7 billion on reportedly over $200 million in ARR, Glean is not inexpensive, but the multiple is arguably more defensible than Palantir’s given the pace of growth. A future public offering would likely depend on continued expansion toward several hundred million in ARR.

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The $250 Trillion AI Hype is Real. A few years from now, you’ll probably wish you’d bought this stock.

When Jeff Bezos said that one breakthrough technology would shape Amazon’s destiny, even Wall Street’s biggest analysts were caught off guard.

Fast forward a year and Amazon’s new CEO Andy Jassy described generative AI as a “once-in-a-lifetime” technology that is already being used across Amazon to reinvent customer experiences.

At the 8th Future Investment Initiative conference, Elon Musk predicted that by 2040 there would be at least 10 billion humanoid robots, with each priced between $20,000 and $25,000.

Do the math. According to Musk, this technology could be worth $250 trillion by 2040.

Put another way, that’s roughly equal to:

  • 175 Teslas
  • 107 Amazons
  • 140 Metas
  • 84 Googles
  • 65 Microsofts
  • And 55 Nvidias

And here’s the wild part — this $250 trillion wave isn’t tied to one company, but to an entire ecosystem of AI innovators set to reshape the global economy.

It’s a leap so massive, it could reshape how businesses, governments, and consumers operate worldwide.

Even if that $250 trillion figure sounds ambitious, major firms like PwC and McKinsey still see AI unlocking multi-trillion-dollar potential.

How could anything be worth that much?

The answer lies in a breakthrough so powerful it’s redefining how humanity works, learns, and creates.

And this breakthrough has already set off a frenzy among hedge funds and Wall Street’s top investors.

What most investors don’t realize is that one under-owned company holds the key to this $250 trillion revolution.

In fact, Verge argues this company’s supercheap AI technology should concern rivals.

Before I reveal the details, let’s talk about how some of the richest people on the planet are positioning themselves.

  • Bill Gates sees artificial intelligence as the “biggest technological advance in my lifetime,” more transformative than the internet or personal computer, capable of improving healthcare, education, and addressing climate change.
  • Larry Ellison — through Oracle, is spending billions on Nvidia chips and partnering with Cohere to embed generative AI across Oracle’s cloud and apps.
  • Warren Buffett — not known for tech hype — says this breakthrough could have a ‘hugely beneficial social impact.

When billionaires from Silicon Valley to Wall Street line up behind the same idea — you know it’s worth paying attention to.

Even as we admire what Tesla, Nvidia, Alphabet, and Microsoft have built, we believe an even greater opportunity lies elsewhere…

But the real story isn’t Nvidia — it’s a much smaller company quietly improving the critical technology that makes this entire revolution possible.

And judging by what I’m hearing from both Silicon Valley insiders and Wall Street veterans…

This prediction might not be bold at all:

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