--- title: "Palantir Ontology Alternative You Can Self-Host and Own" slug: "palantir-ontology-alternative-self-hosted" author: "ibl.ai" date: "2026-11-14 15:00:00" category: "Premium" topics: "Palantir Ontology alternative, Palantir Foundry alternative, self-hosted ontology, semantic layer for AI agents, enterprise knowledge graph, open-source ontology, MCP, Agentic Ontology, data ownership, model-agnostic AI, on-premise AI, air-gapped AI" summary: "A self-hosted Palantir Ontology alternative compared on Palantir's own documentation: what the Foundry Ontology is, where it can run, five open-source layers you can host yourself, and how ibl.ai's MIT-licensed Agentic Ontology maps to object, link and action types." banner: "" thumbnail: "" linkedin: | "What is the best Palantir Ontology alternative we can self-host?" deserves a straighter answer than most comparison pages give it. First, the part competitors skip: Palantir does run on your infrastructure. Its own Apollo documentation says Apollo "supports all major cloud, on-premises, and disconnected (air-gapped) environments," with controls for FedRAMP, IL5 and IL6. So "self-host" is not the dividing line. The dividing line is what you hold when the contract ends. With Foundry you run Palantir's licensed platform, upgraded through Apollo release channels. The Ontology, the object, link and action types that model your business, lives inside it. We compared five layers you can host and keep: ibl.ai's Agentic Ontology (MIT), NVIDIA Auto Ontology (Apache-2.0), Apache Jena (Apache-2.0), TypeDB (MPL-2.0) and Neo4j Community Edition (GPL-3.0). Two of them serve agents over MCP with role-based access; only one also records every tool call in an audit trail and proves its source credentials cannot write. We also say what Palantir does that we do not yet: an approval queue in front of agent write-back is still on our roadmap, and we do not ship an application builder like Workshop. ibl.ai is the other shape: you own all the code and the data, run it model-agnostic across any LLM, pay with no per-seat pricing, and deploy anywhere, from your own cloud to a fully air-gapped network. #iblai #AgenticAI #EnterpriseAI #Palantir #Ontology #KnowledgeGraph #SelfHosted --- ## The Short Answer **The best self-hosted Palantir Ontology alternative depends on what you need to own. ibl.ai's Agentic Ontology is the one built for AI agents: an MIT-licensed knowledge layer that runs inside your network and serves your systems to agents over MCP, so you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing.** Palantir's Ontology is a serious product, and Palantir can deploy it on-premises and in air-gapped networks. Self-hosting alone does not separate the options. What separates them is custody: whether the model of your business is software you license and run under a vendor's management, or source code you hold and change yourself. The sections below compare both on Palantir's own documentation, as of November 2026. ## What is the Palantir Ontology, and what does an alternative have to replace? Palantir's [Ontology overview](https://www.palantir.com/docs/foundry/ontology/overview/) calls the Ontology "an operational layer for the organization." It sits on top of datasets, virtual tables and models in Foundry and connects them to the real-world things they describe. Palantir groups the building blocks as semantic elements (objects, properties, links), kinetic elements (actions, functions, dynamic security) and interfaces. Object and link types map data sources into objects, properties and links. Action types "capture data from operators in your organization." Functions author business logic, and an interface describes "the shape of an object type and its capabilities." A credible Palantir Ontology alternative therefore has to replace two layers, not one. The semantic layer says what exists: entities, attributes, relationships. The operational layer says what can happen: actions, logic and who may do them. Developers reach Palantir's layer through the [Ontology SDK](https://www.palantir.com/docs/foundry/ontology-sdk/overview/), which ships for four channels: npm for TypeScript, pip or Conda for Python, Maven for Java, and an OpenAPI spec for any other language. An alternative needs an equally open door for agents. ## Can you self-host Palantir Foundry's Ontology? Yes, in the sense most buyers mean. Palantir's [Apollo documentation](https://www.palantir.com/docs/apollo/core/introduction/) states that "Apollo supports all major cloud, on-premises, and disconnected (air-gapped) environments," with built-in controls for FedRAMP, IL5 and IL6 accreditation. Any comparison page claiming the Palantir Ontology cannot run on your infrastructure is wrong, and a buyer who checks will stop trusting the rest of it. What self-hosting Foundry means is running Palantir's licensed platform in your environment. Apollo "centrally manages software across independent environments," and each environment's operators subscribe to a release channel through which upgrades arrive. Palantir publishes client libraries openly, for example its [Python platform SDK](https://github.com/palantir/foundry-platform-python) under Apache-2.0, but not the Foundry platform itself. The Ontology your teams build lives inside that platform. So the Palantir Ontology alternative question is really a custody question: when the contract ends, do you still hold the code that models your business, and can your engineers change it without the vendor? ## Which self-hostable Palantir Ontology alternatives exist? Five open-source layers can stand in for some or all of the Palantir Ontology on infrastructure you control. Licences and star counts below are read from each project's GitHub repository on 14 November 2026.
Option Licence GitHub stars What it is What you still build
ibl.ai Agentic Ontology (iblai/ontology) MIT 12 A knowledge layer inside your network that serves databases and SaaS systems to AI agents over MCP, with roles, named operations and an audit trail Connectors for systems outside its catalog; any end-user application
NVIDIA Auto Ontology (NVIDIA/auto-ontology) Apache-2.0 12,743 A Python framework that generates a semantic ontology over relational data and serves it to agents over MCP, CLI and API, with RBAC An audit trail, a read-only safety test on source credentials, and named write operations
Apache Jena (apache/jena) Apache-2.0 1,506 A Java framework for Semantic Web and Linked Data applications on the W3C standards Source-system sync, the operational layer and agent access
TypeDB (typedb/typedb) MPL-2.0 4,513 A strongly typed database for modelling entities, relations and attributes Source-system sync, actions and agent access
Neo4j Community Edition (neo4j/neo4j) GPL-3.0 17,439 A graph database for objects and the links between them Source-system sync, actions, role scoping and agent access
Star counts measure attention, not fit: the least-starred project in the table is ours. Three of the five are components: a graph store or a modelling framework you assemble into an ontology. NVIDIA Auto Ontology also serves agents over MCP with RBAC, but documents no audit trail or proof that its source credentials are read-only. That is a legitimate path when your team wants to build the operational layer itself. The NVIDIA option is covered in more depth in our post on [NVIDIA Auto Ontology and the confident wrong answer](/blog/nvidia-auto-ontology-confident-wrong-answer), including where a generated semantic layer goes wrong. ## How does ibl.ai's Agentic Ontology map to Palantir's object, link and action types? ibl.ai's [Agentic Ontology](/product/agentic-ontology) addresses both layers Palantir's Ontology does, built for agents rather than for analysts. The mapping below uses Palantir's terms on the left and the [iblai/ontology documentation](/developer/guides/ontology) on the right.
Palantir Ontology ibl.ai Agentic Ontology
Object types and properties Tables and API objects your team approves, synced to a local cache with one Markdown file per record and a search index
Link types Relationships discovered from the source systems' keys, then reviewed before anything is served
Action types Named operations your team writes and grants to a role by name; each change is recorded before it runs
Functions Closest equivalent, and narrower: predefined queries your team approves, run through Google MCP Toolbox (in the full deployment); agents cannot send arbitrary SQL to your systems
Ontology SDK One MCP gateway any authorized MCP client can call, under a named role
Deployment A Docker Compose stack on one server or virtual machine in your network
Licence MIT, source on GitHub
Two controls have no direct counterpart in a graph database. Before a database is accepted, seven kinds of write are attempted (create, insert, update, delete, drop, alter, truncate) and all seven must be refused. Every call carries an identity, either a Microsoft Entra ID token, the platform's service token or an ibl.ai credential, and every tool call is logged on your host. Our guide on [how to build an organizational ontology](/blog/how-to-build-an-organizational-ontology) walks through the modelling steps. ## What does Palantir's Ontology do that a self-hosted alternative does not yet? Palantir's Ontology has a mature write path. Its [action types documentation](https://www.palantir.com/docs/foundry/action-types/overview/) says changes to objects, property values and links "will be committed to the Ontology when the user takes the action," captured in a writeback dataset. ibl.ai's Agentic Ontology is read-first by design. Agents only read until a named operation is granted, and the approval queue in front of agent write-back, where an agent proposes and a human approves, is still listed as open work in the project's architecture notes. Palantir also ships end-user applications on the Ontology, such as Object Explorer, Quiver and Workshop. Agentic Ontology ships no application builder; the users are agents, and the applications are whatever your agents and your teams build. If your requirement is the ontology as the place operators record decisions, read our test of [whether an ontology can become the system of record](/blog/can-an-ontology-become-the-system-of-record) before choosing either. ## How do you choose a Palantir Ontology alternative? Four questions sort the Palantir Ontology alternatives quickly, and each has a verifiable answer rather than a feature checklist. **Who holds the code?** With the five options above you hold the source under an MIT, Apache-2.0, MPL-2.0 or GPL-3.0 licence. With Foundry you hold a licence to run Palantir's platform. **Who is the consumer?** If it is analysts and operators in applications, Palantir's Ontology is built for that. If it is AI agents across many models, an MCP-native layer such as ibl.ai's fits the job without a client SDK per language. **What leaves the network?** In iblai/ontology source records stay in your network by default; only answers to authorized requests leave. The exception is LLM-assisted schema mapping: if you turn it on, it sends table and column names and up to five sample rows per table to the provider you choose. The copy agents query and the audit log stay on your host, and embeddings come from ChromaDB's built-in open model running locally. **Who stands behind it?** ibl.ai is family-owned and operated from New York, NY — a U.S.-headquartered, domestically-owned long-term partner, not a vendor that sells licenses and moves on. Our [AI Transformation](/service/ai-transformation) engagement delivers the ontology first. The ibl.ai platform it plugs into is proven at scale: 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University. The same layer is the subject of our explainer on the [semantic layer for AI agents](/blog/semantic-layer-for-ai-agents), which covers why agents need one at all. ## Frequently Asked Questions ### What is the best self-hosted alternative to the Palantir Ontology? For AI agents, ibl.ai's Agentic Ontology: MIT-licensed, deployed as a Docker Compose stack in your network, and served to agents over MCP with role-scoped access and an audit trail. For a component to build on yourself, Apache Jena, TypeDB or Neo4j Community Edition; NVIDIA Auto Ontology is a fuller layer focused on NL-to-SQL over relational data. ### Can Palantir Foundry run on-premises or air-gapped? Yes. Palantir's Apollo documentation says it supports all major cloud, on-premises and disconnected (air-gapped) environments, with controls for FedRAMP, IL5 and IL6. You run Palantir's licensed platform there; the platform source is not published. ### Is ibl.ai's Agentic Ontology open source? Yes. The code is at github.com/iblai/ontology under the MIT licence, so your engineers can read, modify, extend or replace any part of it. ### Does the ibl.ai ontology copy data out of my network? By default, source records do not leave it. The ontology reads source systems with read-only access and keeps its copy, search index and audit log on a server you own; what leaves is the answer to each authorized agent request. Roles, sync schedules and system metadata such as table names can optionally be kept in your ibl.ai platform instead. If you enable LLM-assisted schema mapping, it sends table and column names and up to five sample rows per table to your chosen provider. --- *Sources, all read for this post on 14 November 2026: Palantir's definition and building blocks of the Ontology from its [Ontology overview](https://www.palantir.com/docs/foundry/ontology/overview/); the writeback behaviour from its [action types overview](https://www.palantir.com/docs/foundry/action-types/overview/); the four SDK channels from the [Ontology SDK overview](https://www.palantir.com/docs/foundry/ontology-sdk/overview/); the supported environments, accreditations and release-channel model from the [Apollo introduction](https://www.palantir.com/docs/apollo/core/introduction/); and every licence from the projects' own GitHub repositories, linked in the table. ibl.ai's behaviour is from the [iblai/ontology documentation](/developer/guides/ontology). No Palantir price is quoted: we found no published list price to cite.* ## Why does owning the AI stack matter? **ibl.ai is the agentic AI platform where you own all the code and the data. You self-host the entire stack inside your own perimeter, run it model-agnostic across any LLM and switch anytime, and pay by usage with no per-seat pricing — so you can deploy anywhere: your cloud, on-premise, GovCloud, or fully air-gapped.** - **You own all the code and the data.** Full source code under a perpetual license, running on your infrastructure. Not API access to someone else's platform — the stack itself is yours. - **Model-agnostic.** Run any LLM — Claude, GPT, Gemini, Llama, Command, or your own fine-tune — and switch providers without rewriting the platform. - **No per-seat pricing.** Usage-based billing against a budget cap you set. Cost tracks what your organization actually uses, not how many people you employ. - **Deploy anywhere.** Your cloud, your VPC, on-premise, GovCloud, or a fully air-gapped network with no outbound connectivity. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University. ibl.ai is family-owned and operated from New York, NY — a U.S.-headquartered, domestically-owned long-term partner, not a vendor that sells licenses and moves on.