What this blog is about

AI map Ontology is a technical blog covering Palantir Foundry, AIP, and Ontology-based enterprise data use.

Companies are quickly adopting personal-productivity AI — coding assistants, document summarizers — but “AI that actually understands and uses our company’s data” often stalls at the pilot stage. This blog breaks down why that gap exists, and how semantic structures like Ontology can bridge it, from a practitioner’s point of view.

Topics covered

• Palantir Guides: Foundry data integration, AIP (AI Platform), and other platform concepts explained
• Ontology in Practice: Core ontology concepts (Object, Link, Action) and enterprise data modeling methodology
• Enterprise AI: Moving beyond personal-productivity AI toward data-driven decision making
• Field Notes: Lessons learned while actually running this — cases are generalized and anonymized

Why this blog exists

This blog is run for two reasons.

1. Organizing knowledge: Systematically documenting practical Palantir and Ontology knowledge.
2. Sharing accurate information: The goal is to convey genuinely useful technical perspective, without hype or promotional content.

Who runs this

This blog is run by someone with 20+ years of hands-on experience in enterprise IT and data organizations. After years working with traditional BI and reporting tools like SAP BI and Qlik Sense, the last 1–2 years have been spent directly on Palantir Foundry projects — designing ontologies and migrating them from legacy systems, building data connections and pipelines, developing agents and logic with AIP, and moving existing reporting and dashboards onto the Foundry stack. This blog is where that hands-on experience — what worked, what didn’t, and why — gets organized through the lens of Ontology and enterprise AI. Practical examples described here are based on real experience, but all information that could identify a specific organization, company name, or project has been removed and generalized.

Content principles

• Palantir’s official materials or third-party work are never reproduced verbatim — concepts are understood first, then written in the author’s own words.
• No confidential company information, internal projects, or customer data is discussed.
• No content about stock price or investment. This is a technical blog and does not provide investment advice.

For inquiries, please reach out via the Contact page.