Thought Leadership

Palantir has built something genuinely remarkable. Their Ontology concept — mapping an entire organisation as a digital twin where AI agents make decisions against real operational data — is the most sophisticated approach to enterprise intelligence on the market. The AIP Bootcamps, where prospects build functional AI use cases on their own data in five days, have a roughly 75% conversion rate. That is not marketing hype. That is product-market fit.

But there is a structural gap in Palantir's model that matters enormously for mid-market companies. It is a gap that has nothing to do with the quality of their technology and everything to do with who it was designed for — and what happens after the intelligence is delivered.

What Palantir Gets Right

Credit where it is due. Palantir has solved several problems that the rest of the enterprise AI industry is still struggling with.

The Ontology is genuinely world-class business modelling. Instead of treating data as tables in a warehouse, Palantir maps your business as interconnected objects — customers, orders, shipments, suppliers, contracts — with relationships and logic that mirror how your organisation actually operates. This is a fundamentally better abstraction than what Databricks or Snowflake offers, and it enables AI agents to reason about your business rather than just query your data.

AIP Bootcamps are a brilliant go-to-market strategy. The 75% conversion rate is extraordinary in enterprise software, where most sales cycles last six to twelve months. Palantir compresses the evaluation period to five days and lets the prospect's own data make the argument. It is one of the most effective product-led sales motions in enterprise technology.

Decision intelligence is real. Palantir's AI agents do not just surface dashboards. They make operational recommendations — reroute this shipment, flag this transaction, accelerate this order — against live data. This is a meaningful step beyond the business intelligence tools that most companies are still using.

The government and defence pedigree is battle-tested. Whatever your views on Palantir's defence contracts, the result is a platform that has been stress-tested at a scale and with security requirements that few commercial vendors can match. Their recent pivot to commercial enterprise is backed by technology that works under extreme conditions.

The Mid-Market Reality

Here is where the picture becomes more complicated for companies in the $20M to $200M revenue range.

Pricing starts at roughly $1M per year and scales from there. This is entirely appropriate for a Fortune 500 company that will deploy the Ontology across dozens of business units. For a $50M company where the entire IT budget might be $2M, it is a different calculation entirely.

Deployment complexity requires a data engineering team. The Ontology is powerful precisely because it is comprehensive — but building and maintaining it requires engineers who understand both Palantir's platform and your business domain. Most mid-market companies do not have that team, which means hiring one or engaging a systems integrator. Either path adds cost and time.

The AIP Bootcamps are free, but conversion leads to enterprise pricing. The five-day workshop is genuinely valuable. But the implicit next step is a six- or seven-figure annual contract. For companies that loved what they saw in the Bootcamp but cannot justify that spend, there is no middle path.

And then there is the critical gap — the one that matters most.

Palantir tells you what to do, but it does not build the software to do it. The Ontology can identify that your client onboarding process takes five to ten days and should take two hours. The AI agents can recommend exactly which steps to automate and in what order. But the onboarding automation system still needs to be built — by your engineering team, or by EPAM, or by Thoughtworks. For a $50M to $150M company, Palantir is like buying a Formula 1 engine for a car that does not exist yet.

The Software Gap

This is not a problem unique to Palantir. It is an architectural pattern across the entire enterprise intelligence category.

Palantir, Databricks, Snowflake, and C3.ai all share the same structural gap: they give you the brain but not the hands. They surface the insight but do not build the operational system. They are enormously valuable at the intelligence layer — and they leave a chasm between the insight and the action.

Your analysts can see that 12% of logistics cost is being wasted on suboptimal routing. Your operations team can see that three compliance workflows could be fully automated. Your sales leaders can see which accounts are most likely to churn in the next quarter. The intelligence is there. It is accurate. It is actionable.

But the routing optimisation system still needs to be built. The compliance automation still needs to be engineered. The churn intervention workflow still needs to be designed, developed, tested, and deployed. And somebody else has to do that work — on a different timeline, with a different vendor, at a different price point.

For Fortune 500 companies with large engineering organisations, this gap is manageable. They already have the teams and the budgets. For mid-market companies, the gap is often where the entire initiative stalls. The Bootcamp was brilliant. The board was convinced. The contract was signed. And then the intelligence sat in a dashboard while the company searched for an engineering partner to build the systems that would actually change operations.

What a Closed-Loop Alternative Looks Like

At Xamun, we built a system that addresses the gap directly — not by competing with Palantir's intelligence (which is genuinely excellent) but by solving the problem that Palantir's architecture does not address.

Xamun Intelligence (XI) provides mid-market-accessible business intelligence: market signals, competitor movements, operational data analysis, and objective tracking. It produces an Opportunity Map, a Found Budget that quantifies recoverable spend, and a Transformation Roadmap that sequences the work by impact and feasibility. It is not as deep as Palantir's Ontology for complex enterprise modelling — but it is designed for the $20M to $200M company that needs actionable intelligence without a data engineering team to deploy it.

The Software Factory builds the systems that operationalise the insights. When XI identifies that client onboarding should take two hours instead of five days, the Factory builds the onboarding automation system in two to four weeks. AI handles specification generation, code scaffolding, and testing. Expert humans handle architecture, business logic, and compliance review. Stakeholders approve the specification before development begins.

The loop closes continuously. XI tracks the outcomes of deployed software, surfaces new opportunities based on the data that the new systems generate, and feeds them back into the Factory. Each deployment generates new data, which sharpens the next round of intelligence, which informs the next build.

The comparison is not "Xamun is better than Palantir." It is "Xamun solves the problem Palantir does not address for companies that cannot afford both Palantir AND an engineering firm to build the software that acts on the intelligence."

The Honest Assessment

Different companies need different solutions. Here is how we see the landscape honestly:

If you are $500M+ with a data engineering team, Palantir is probably the right choice. The Ontology's depth at enterprise scale is unmatched. You have the engineers to deploy it, the budget to sustain it, and the organisational complexity that justifies it. You can pair it with your existing engineering capacity or an IT services firm to build the operational systems.

If you are $50M to $200M and need both intelligence and execution, Xamun collapses both into one system. You get actionable intelligence at a price point designed for your budget, and the software to act on it is built in the same engagement. No handoffs between vendors. No six-month gap between insight and action.

If you have done a Palantir Bootcamp and loved the intelligence but cannot justify $1M per year, XI is designed for you. It provides the continuous business intelligence that made the Bootcamp compelling — market signals, operational analysis, competitive positioning — at a fraction of the cost, with the software delivery capability that Palantir does not offer.

The Next Step for Enterprise AI

The future of enterprise AI is not intelligence or execution. It is both, in one loop.

Palantir proved something important: that AI-driven business intelligence works. That mapping an organisation as a digital twin and letting AI agents make operational decisions is not science fiction — it is production-grade technology that delivers measurable results. The AIP Bootcamps proved that when prospects experience intelligence on their own data, the value proposition sells itself.

The next step is connecting that intelligence to the software that acts on it. Not as a separate engagement with a separate vendor on a separate timeline — but as a continuous loop where insight and action are part of the same system.