GleanEnterprise
An enterprise AI platform that connects to company apps to power permission-aware search, an assistant, and agents over internal knowledge.
AI / LLM comparison
Glean vs Palantir AIP
Pricing, pros, cons, and ideal use cases — side by side.
Palantir AIPEnterprise
Connects LLMs to a governed model of your business — the Ontology — so agents act on real operational objects instead of loose documents.
At a glance
| Glean | Palantir AIP | |
|---|---|---|
| Pricing | EnterpriseEnterprise pricing, quoted per organization and typically seat-based. | EnterpriseNot published — enterprise contracts negotiated directly, typically as a platform agreement rather than seats. The AIP Bootcamp is the standard entry point: bring your own data and build working use cases in days before committing. Budget for the data integration work, which is usually the larger number. |
| Category | AI / LLM | AI / LLM |
| Ideal for | Large enterprises with knowledge spread across many toolsTeams deploying an internal AI assistantOrganizations that need permission-aware AI search | Large enterprises running AI against core operational processesSupply chain, manufacturing, and logistics operations teamsRegulated industries needing full audit trails on AI decisionsOrganisations already running Palantir Foundry |
Pros & cons
Glean
Pros
- Permission-aware search across the whole app estate
- Mature connector library for enterprise SaaS
- Assistant and agent layer on a trusted knowledge graph
- Strong fit for large, complex organizations
Cons
- Enterprise pricing and a real procurement process
- Value depends on broad connector deployment
- Overkill for small teams or simple stacks
Palantir AIP
Pros
- The Ontology gives agents a governed model of the actual business
- Built for operational decisions, not document chat
- Governance, audit, and access control are native, not add-ons
- Model-agnostic — you are not locked to one LLM vendor
- Bootcamp model produces working results in days rather than a long pilot
Cons
- The deepest platform commitment on this list — switching cost is near total
- No published pricing and a heavyweight commercial relationship
- Value depends on data integration work you have to do regardless
- Far too much platform for anything below large-enterprise scale
- Requires internal capability to build and maintain ontology and workflows
Which should you choose?
Glean is built around large enterprises with knowledge spread across many tools; Palantir AIP leans more toward large enterprises running ai against core operational processes. Shortlist the one whose strengths line up with your biggest constraint.
Still deciding between Glean and Palantir AIP?
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