AI Insights
Prediction: This Artificial Intelligence (AI) Player Could Be the Next Palantir in the 2030s

Becoming the next Palantir is a tough job.
Palantir (NASDAQ: PLTR) has already shown what it takes to be a successful enterprise artificial intelligence (AI) player: Become the core platform for customers to build their AI applications on, rapidly turn pilot projects into production-level deployments, cross-sell and upsell to existing clients, and focus on new client acquisition across industries and new verticals.
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Innodata (INOD 2.53%) is much smaller, but it seems to be on a similar growth trajectory. The company is moving beyond traditional data services and is now becoming an AI partner focused on the data and evaluation layer in the enterprise AI stack — something that Palantir is not focusing on.
Financial performance
Palantir’s second-quarter fiscal 2025 (ending June 30) earnings performance underscores the success of this business model. Revenues grew 48% year over year to over $1 billion, with U.S. commercial and U.S. government revenues soaring year over year by 93% and 53%, respectively. The company’s Rule of 40 score increased 11 percentage points sequentially to 94. Management raised its fiscal 2025 revenue guidance and ended Q2 with total contract value (TCV) of $2.3 billion.
Innodata’s Q2 of fiscal 2025 (ending June 30) performance was also stellar. Revenues grew 79% year over year to $58.4 million, while adjusted EBITDA increased 375% to $13.2 million. Management raised full-year organic growth guidance to 45% or more, driven by a robust project pipeline, with several projects from large customers.
Data vendor to AI partner
Palantir differs from other AI giants by focusing not on large language models, but on its ability to leverage AI capabilities to resolve real-world problems. The company’s focus on ontology — a framework relating the company’s real assets to digital assets — helps its software properly understand context to deliver effective results.
Innodata also seems to be implementing a similar strategy. Instead of focusing on traditional data and workflows, it is providing “smart data,” or high-quality complex training data, to improve accuracy, safety, coherence, and reasoning in AI models of enterprise clients. It is also working closely with big technology customers to test models, find performance gaps, and deliver the data and evaluation needed to raise model performance. That shift will help Innodata’s offerings become entrenched in their clients’ ecosystems, thereby strengthening pricing power and creating a sticky customer base.
Vendor neutrality
Palantir has not built any proprietary foundational model. Plus, its Foundry and artificial intelligence platform (AIP) can run on any cloud and can be integrated with multiple large language models. By giving its clients the flexibility to choose their preferred cloud infrastructure and AI models, the company prevents vendor lock-in. This vendor neutrality has helped build trust among both government and commercial clients.
Innodata’s vendor-neutral stance is also becoming a competitive advantage. In its Q2 earnings call, an analyst noted that several big technology companies have said they would no longer work with Innodata’s largest competitor, Scale AI, after Meta Platforms’ large investment in the company. This is creating new opportunities for Innodata. Because it isn’t tied to any single platform, there is no conflict of interest involved in working with Innodata. This gives enterprises and hyperscalers confidence that their proprietary data and model development efforts will not be compromised.
Scaling efforts
Palantir’s business is seeing rapid traction, driven primarily by high-value clients. The company closed 157 deals worth $1 million or more, of which 42 deals were worth $10 million or more.
Innodata is scaling up revenues while also focusing on profitability. Management highlighted that it has won several new projects from its largest customer. The company has also expanded revenues from another big technology client, from $200,000 over the past year to an expected $10 million in the second half of 2025. Innodata’s adjusted EBITDA margins were 23% in the second quarter, up from 9% the same quarter of the prior year.
Agentic AI
Palantir has been focusing on the agentic AI opportunity by investing in AI Function-Driven Engineering (FDE) capability within its AIP platform. AI FDE is expected to solve bigger and more complex problems for clients by autonomously executing a wide array of tasks, including building and changing ontology, building data flows, writing functions, fixing errors, and building applications. It also works in collaboration with humans and can help clients get results faster. Palantir is thus progressing toward developing AI systems that can plan, act, and improve inside enterprise setups.
Innodata is also advancing its agentic AI capabilities by helping enterprises build and manage AI that can act autonomously. The company aims to provide simulation training data to show how humans solve complex problems, and advanced trust and safety monitoring to guide these systems. Agentic AI is also expected to help the robotics field progress rapidly, and AI systems will run on edge devices used in daily life. Hence, Innodata plans to invest more in building data and evaluation services for these agentic AI and robotics projects, which it expects could become a market even larger than today’s post-training data work.
Valuation
Despite its many strengths, Innodata is still very much in the early stages of its AI journey. Shares have gained by over 315% in the last year. Yet, with a market cap of about $1.9 billion and trading at nearly 8.2 times sales, Innodata is priced like a data services company making inroads in the AI market, and not like an AI platform company with a significant competitive moat. On the other hand, Palantir stock is expensive and trades closer to 114 times sales. This shows how Wall Street rewards a category leader like Palantir, whose offerings act as an operating layer for enterprise AI companies.
Innodata also needs to dominate the AI performance market to reach such sky-high valuations. The company will need to expand its customer base, cross-sell and upsell to existing clients, and make it difficult to switch to the competition.
While this involves significant execution risk, there is definitely a chance — albeit a small one — that Innodata can become the next Palantir in the 2030s.
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Why AI is never going to run the world

The secret to human intelligence can’t be replicated or improved on by artificial intelligence, according to researcher Angus Fletcher.
Fletcher, a professor of English at The Ohio State University’s Project Narrative, explains in a new book that AI is very good at one thing: logic. But many of life’s most fundamental problems require a different type of intelligence.
“AI takes one feature of intelligence – logic – and accelerates it. As long as life calls for math, AI crushes humans,” Fletcher writes in the book “Primal Intelligence.”
“It’s the king of big-data choices. The moment, though, that life requires commonsense or imagination, AI tumbles off its throne. This is how you know that AI is never going to run the world – or anything.”
Instead, Fletcher has developed a program to help people develop their primal intelligence, a program that has been successfully used with groups ranging from the U.S. Army to elementary school students.
At its core, primal intelligence is “the brain’s ancient ability to act smart with limited information,” Fletcher said.
In many cases, the most difficult problems people face involve situations where they have limited information and need to develop a novel plan to meet a challenge.
The answer is what Fletcher calls “story thinking.”
“Humans have this ability to communicate through stories, and story thinking is the way the brain has evolved to work,” he said.
“What makes humans successful is the ability to think of and develop new behaviors and new plans. It allowed our ancestors to escape the predator. It allows us to plan, to plot our actions, to put together a story of how we might succeed.”
Humans have four “primal powers” that allow us to act smart with little information.
Those powers are intuition, imagination, emotion and commonsense. In the book, Fletcher expands on each of these and the role they have in helping humans innovate.
In essence, he says these four primal powers are driven by “narrative cognition,” the ability of our brain to think in story. Shakespeare may be the best example of how to think in story, he said.
Fletcher, who has an undergraduate degree in neuroscience and a PhD in literature, discusses in the book how Shakespeare’s innovations in storytelling have inspired innovators well beyond literature. He quotes people from Abraham Lincoln to Albert Einstein to Steve Jobs about the impact reading Shakespeare had on their lives and careers.
Many of Shakespeare’s characters are “exceptions to rules” rather than archetypes, which encourages people to think in new ways, Fletcher said.
What Shakespeare has helped these pioneers – and many other people – do is see stories in their own lives and imagine new ways of doing things and overcoming obstacles, he said.
That’s something AI can’t do, he said. AI collects a lot of data and then works out probable patterns, which is great if you have a lot of information.
“But what do you do in a totally new situation? Well, in a new situation you need to make a new plan. And that’s what story thinking can do that AI cannot,” he said.
The U.S. Army was so impressed with Fletcher’s program that it brought him in to help train soldiers in its Special Operations unit. After seeing it in action, the Army awarded Fletcher its Commendation Medal for his “groundbreaking research” that helped soldiers see the future faster, heal quicker from trauma and act wiser in life-and-death situations.
In the book, Fletcher gave an example of how one Army recruit used his primal intelligence to overcome obstacles in the most literal sense.
As part of its curriculum, Army Special Operations had a final test for recruits: an obstacle course of logs and ropes. The recruits were told they had the ring the bell at the end of the course before time expires in order to pass the test.
This particular recruit knew he couldn’t beat the clock. At the starting line, he thought of a new plan: he ran around the obstacle course, rather than through it, ringing the bell in record time.
While other military schools would have flunked him, Special Operations passed him, based on his ingenuity in passing the test, Fletcher said. As the Army monitored his career after graduation, it found he outperformed many of his classmates on field missions.
The value of primal intelligence works in all walks of life, including business. While business often emphasizes management, Fletcher said primal intelligence shines when leadership is needed.
“Management is optimizing existing processes. But the main challenge of the future is not optimizing things that already work,” Fletcher said.
“The challenge of the future is figuring things out when we don’t know what works. That’s what leadership is all about, and that’s what story thinking is all about.”
In business and elsewhere, Fletcher said AI has a role. But it should not be seen as a replacement for human intelligence.
“Humans are able to say, this could work but it hasn’t been tried before. That’s what primal intelligence is all about,” he said.
“Computers and AI are only able to repeat things that have worked in the past or engage in magical thinking. That’s not going to work in many situations we face.”
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