VS

Purpose-built for the AI era.

Not retrofitted from the last one.

Palantir built Gotham and Foundry for government intelligence. They added AIP in 2023 and called it enterprise AI. But a proprietary Ontology, consulting-heavy bootcamps, and 7-figure deals designed for Fortune 500 don't serve the 95% of enterprises that actually need AI infrastructure. Rebase was built for them.

The question isn't whether Palantir is impressive. It's whether it's right for your use case.

The question isn't whether Palantir is impressive. It's whether it's right for your use case.

What Palantir Built

Founded 2003. Gotham for government intelligence, foundry for commercial, Apollo for deployment, AIP added as a bolt-on AI layer in 2023. At the core: a proprietary Ontology a relationships. Powerful, but closed. Once your knowledge is modeled in Palantir’s format, migration is prohibitively expensice. That’s by design.

What Rebase Provides

Enterprise AI Infrastructure designed for the LLM era. Context Engine Builds an open knowledge graph via APIs, CLI, and MCP. AI gateway any model, any provider, BYOK. Agent Studio for no-code and pro-code agent building. Memory system for persistent institutional intelligence. Self-serve deployment in your cloud. Your data stays in your environment.

Head-to-Head Comparison

Head-to-Head Comparison

Dimension

Palantir AIP

Rebase

Architecture

Founded 2003. Gotham/Foundry/Apollo + AIP bolt-on (2023). Proprietary Ontology at core.

Built 2024. Every component designed for the LLM era. AI-native throughout.

Core Data Model

Proprietary Ontology. Powerful but closed. Once modeled, migration is prohibitively expensive.

Open knowledge graph via APIs, CLI, MCP. You own your data model. You can always leave.

Lock-In

139% NRR. High switching costs make leaving financially impractical. Expansion driven by dependency, not just value.

Open standards. Knowledge graph compounds value, but architecture is portable. Expansion driven by choice.

Deployment

Bootcamps: 5-day workshops with forward-deployed engineers. Consulting-heavy model.

Self-serve. Your team deploys. Support available, never mandatory.

Commercial vs. Gov

55% government revenue. Commercial growing but still proving the model outside defense and intelligence.

Commercial-first from day one. Healthcare, financial services, utilities, telecom.

Model Access

Third-party LLMs through Palantir's governance layer. Model-agnostic in theory, everything through their inter-mediary.

AI Gateway. Any LLM, any provider, BYOK. Direct access, no intermediary.

Target Customer

Fortune 500 + government agencies. ~3,000 employees serving global clients. Premium-only market.

200-10K employee enterprises. Companies that need AI infrastructure without 7-figure overhead.

Deployment Speed

Months to quarters. Requires bootcamps, forward-deployed engineers, custom integrations.

Weeks. Self-serve. Your cloud. No mandatory consulting.

Business Model

Custom, usage-based. 6-7 figure deals plus bootcamps, FDE time, ongoing dependency.

Predictable infrastructure pricing. No hidden dependency. Transparent and accessible.

Head-to-Head Comparison

Dimension

Palantir AIP

Rebase

Architecture

Founded 2003. Gotham/Foundry/Apollo + AIP bolt-on (2023). Proprietary Ontology at core.

Built 2024. Every component designed for the LLM era. AI-native throughout.

Core Data Model

Proprietary Ontology. Powerful but closed. Once modeled, migration is prohibitively expensive.

Open knowledge graph via APIs, CLI, MCP. You own your data model. You can always leave.

Lock-In

139% NRR. High switching costs make leaving financially impractical. Expansion driven by dependency, not just value.

Open standards. Knowledge graph compounds value, but architecture is portable. Expansion driven by choice.

Deployment

Bootcamps: 5-day workshops with forward-deployed engineers. Consulting-heavy model.

Self-serve. Your team deploys. Support available, never mandatory.

Commercial vs. Gov

55% government revenue. Commercial growing but still proving the model outside defense and intelligence.

Commercial-first from day one. Healthcare, financial services, utilities, telecom.

Model Access

Third-party LLMs through Palantir's governance layer. Model-agnostic in theory, everything through their inter-mediary.

AI Gateway. Any LLM, any provider, BYOK. Direct access, no intermediary.

Target Customer

Fortune 500 + government agencies. ~3,000 employees serving global clients. Premium-only market.

200-10K employee enterprises. Companies that need AI infrastructure without 7-figure overhead.

Deployment Speed

Months to quarters. Requires bootcamps, forward-deployed engineers, custom integrations.

Weeks. Self-serve. Your cloud. No mandatory consulting.

Business Model

Custom, usage-based. 6-7 figure deals plus bootcamps, FDE time, ongoing dependency.

Predictable infrastructure pricing. No hidden dependency. Transparent and accessible.

Why Enterprises Choose Rebase

Why Enterprises Choose Rebase

Built for the AI era. Not bolted onto legacy architecture.

Palantir was built for government intelligence analysis in 2003. AIP is a bolt-on layer added 20 years later — not a rebuild. Every platform is constrained by its foundation. Rebase was designed for the LLM era from scratch — no legacy architecture, no retrofit.

Open standards. Your data model belongs to you.

Palantir's Ontology is proprietary. Once your organizational knowledge is modeled in their format, migration is prohibitively expensive. Rebase uses MCP, standard APIs, and CLI. Your knowledge graph compounds value over time, but it's built on open standards you can inspect, extend, export, and migrate.

A platform your team deploys. Not a consulting engagement.

Palantir's bootcamps with forward-deployed engineers are a consulting model. If the vendor needs to be on-site for every deployment, that's a services company. Rebase is a platform your team deploys in weeks. If we need to be on-site to make it work, we've failed.

Commercial DNA. Built for enterprises, not intelligence agencies.

Palantir's core competency is government intelligence — defense, counterterrorism, battlefield analytics. A hospital system going through AI transformation doesn't need intelligence tools retrofitted for healthcare. Rebase was built for tech-complex commercial enterprises from day one.

Customers should expand because they want to. Not because they can't leave.

Palantir's 139% NRR is driven in part by high switching costs. Rebase believes in earning expansion through product value. If we don't deliver, you should be able to leave. If we do, you'll expand because you choose to — not because your data is locked in a proprietary format.

What Palantir's model tells you about the enterprise AI market.

What Palantir's model tells you about the enterprise AI market.

Palantir built a 20-year-old platform for government intelligence, added an AIP layer in 2023, and is now selling it as commercial AI infrastructure. Their Ontology is powerful but it's also a proprietary format that makes leaving financially impractical. Their bootcamp model puts Palantir engineers on-site for every deployment. Their stock trades at ~200x earnings with analyst price targets ranging from $50 to $260.

None of this makes Palantir bad. It makes them a specific solution for a specific market Fortune 500 and government agencies with 7-figure budgets and tolerance for proprietary platforms. The question for the other 95% of enterprises is whether that model serves them, or whether AI-native infrastructure with open standards is a better foundation for the next five years.

When Each Makes Sense

When Each Makes Sense

Palantir Makes Sense If

  • Fortune 500 or government agency with 7-figure AI budget

  • Defense or intelligence use cases

  • Comfortable with proprietary platform and high switching costs

  • Can support mandatory boot camps and forward-deployed engineer teams

  • Need Palantir's specific government certifications

OR

Choose Rebase When

  • 200-10K employee enterprise without 7-figure overhead budget

  • Want open standards — inspect, extend, export, migrate your data

  • Need self-serve deployment in weeks, not bootcamp quarters

  • Commercial enterprise: healthcare, financial services, utilities, telecom

  • Data must stay in your environment — BYOC, on-prem, air-gapped

  • Making an architecture decision for the next five years

When Each Makes Sense

Palantir Makes Sense If

  • Fortune 500 or government agency with 7-figure AI budget

  • Defense or intelligence use cases

  • Comfortable with proprietary platform and high switching costs

  • Can support mandatory boot camps and forward-deployed engineer teams

  • Need Palantir's specific government certifications

OR

Choose Rebase When

  • 200-10K employee enterprise without 7-figure overhead budget

  • Want open standards — inspect, extend, export, migrate your data

  • Need self-serve deployment in weeks, not bootcamp quarters

  • Commercial enterprise: healthcare, financial services, utilities, telecom

  • Data must stay in your environment — BYOC, on-prem, air-gapped

  • Making an architecture decision for the next five years

Why Teams Choose Rebase

Why Teams Choose Rebase

DEPLOY IN WEEKS, NOT MONTHS

No bootcamps. No forward-deployed engineers. Your team deploys in your cloud, on your terms.

MEASURABLE IMPACT

Up to 80% reduction in manual data sync. 60% faster engineering delivery. Replace 3-5 point solutions with one platform.

ENTERPRISE READY

SOC 2 Type II. 50+ native integrations. Zero data retention. BYOC/on-prem/air-gapped. HIPAA and GDPR ready.

FAQS

REBASE vs Palantir

REBASE vs Palantir

We're evaluating Palantir AIP. Why should we also look at Rebase?

Palantir AIP is designed for Fortune 500 and government agencies with 7-figure budgets and tolerance for proprietary platforms. If that's you, it's a strong option. But if you're a 200-10K employee enterprise that needs AI infrastructure without the Palantir overhead — proprietary lock-in, mandatory bootcamps, consulting-heavy deployment — Rebase gives you comparable capabilities with open standards, self-serve deployment, and predictable pricing.

How is Rebase's knowledge graph different from Palantir's Ontology?

Is Rebase enterprise-ready compared to a platform like Palantir?

Can we use Rebase alongside Palantir, or is it one or the other?

We have complex enterprise systems. Can Rebase actually handle that?

Ready to build on
AI-native infrastructure?

Ready to build on
AI-native infrastructure?

Open standards. Your cloud. Live in weeks. No proprietary lock-in.

Ready to build on
AI-native infrastructure?

Open standards. Your cloud. Live in weeks. No proprietary lock-in.

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