PRACTICAL GUIDES FOR ENTERPRISE AI

기업 데이터를
AI가 이해하게 만드는
실무 지식의 지도

온톨로지, Foundry, AIP를 개념부터 실제 설계 의사결정까지 연결합니다.

Making Enterprise Data
Understandable to AI
— A Practical Knowledge Map

Connecting Ontology, Foundry, and AIP from core concepts to real design decisions.

Build with AI

AI를 업무 흐름 안에 설계하기

단순 챗봇이 아닌, 데이터·사용자 경험·에이전트를 함께 설계하는 글입니다.

Build with AI

Designing AI into your workflow

Not just a chatbot — articles on designing data, UX, and agents together.

AI Agent series

한 편씩 따라가는 AI Agent 학습

팔란티어를 몰라도 시작할 수 있습니다
Enterprise AI

도입 전에 답해야 할 질문

기술 유행이 아니라 기업 데이터와 의사결정의 관점에서 AI 도입을 검토합니다.

Enterprise AI

Questions to answer before you adopt

We look at AI adoption from the angle of enterprise data and decision-making, not hype.

EDITORIAL PRINCIPLES

빠른 답보다
검증 가능한 해를

공식 문서와 실제 설계 맥락을 바탕으로, 이해하기 쉬운 언어로 다시 설명합니다.

모든 글에 참고한 공식 문서 링크와 마지막 검토일을 함께 표기합니다
개념 설명 부분과, 실제 프로젝트에서 판단이 필요한 부분을 섞지 않고 구분해서 씁니다
내용에 오류가 있으면 정정을 요청할 수 있도록 익명 문의 채널을 열어둡니다
EDITORIAL PRINCIPLES

Verifiable answers,
not fast ones

Re-explained in plain language, grounded in official docs and real design context.

Every post lists the official docs it references and its last review date
Conceptual explanation is kept separate from judgment calls that depend on your specific project
An anonymous contact channel is kept open so errors can be reported and corrected

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Foundry·온톨로지·기업 AI를 이해하는 데 도움이 되는 실전 메모와 가이드입니다.

Latest Articles

Practical notes and guides to help you understand Foundry, Ontology, and enterprise AI.

  • Data Lineage: Tracing Data Provenance in Palantir Foundry

    Data Lineage: Tracing Data Provenance in Palantir Foundry
    How Foundry’s Data Lineage feature tracks upstream/downstream data flow, column-level lineage, and security marking inheritance.

  • Object Explorer vs Quiver vs Contour: Choosing the Right Tool

    Object Explorer vs Quiver vs Contour: Choosing the Right Tool
    A side-by-side comparison of Foundry’s three exploration and analysis tools, with practical criteria for when to use each.

  • Why Enterprise AI Stalls at the Chatbot Stage

    Why Enterprise AI Stalls at the Chatbot Stage
    Who This Article Is For The chatbot pilot went smoothly. Then, right before a company-wide rollout, it just stopped. This is for anyone who’s run an internal chatbot pilot and hit a wall at the actual deployment stage — or a practitioner who just got asked, “let’s build a chatbot on our company data too.” […]

  • What Is Palantir AIP? The AI Layer Built Into Foundry

    What Is Palantir AIP? The AI Layer Built Into Foundry
    Summary — AIP (AI Platform) is the generative-AI layer built into Palantir Foundry, using the Ontology as context to run LLMs safely on top of enterprise data. Unlike wiring a general-purpose LLM API in directly, it comes with permissions (RBAC), audit logs, and a choice of models, and features like Assist, Logic, Chatbot Studio, and […]

  • Foundry Data Integration Guide: Data Connections to Pipelines

    Foundry Data Integration Guide: Data Connections to Pipelines
    Who This Article Is For This is for data engineers evaluating or just starting on Foundry, or anyone who’s heard plenty about the Ontology but is curious how data actually gets in before any of that. If you’ve worked with ERP or internal system integrations, comparing this against familiar concepts like ETL and connectors will […]

  • FDE vs. PI Consultant vs. Solution Architect: The Real Difference

    FDE vs. PI Consultant vs. Solution Architect: The Real Difference
    Summary — FDE, PI Consultant, and Solution Architect all work somewhere between the business and the technology, but what they actually produce and how far their responsibility extends differ quite a bit. An FDE ships a working application, a PI Consultant redesigns and gets sign-off on a business process, and a Solution Architect designs structure […]

  • Designing AI Agents and Workflows in AIP: FDE and Logic

    Designing AI Agents and Workflows in AIP: FDE and Logic

    Using a purchase order approval workflow as the example, walk through how AI FDE drafts it and AIP Logic turns that draft into an executable business process.


  • 3 Ways to Design AI User Experience in AIP

    3 Ways to Design AI User Experience in AIP

    Personal work support, a shared front door for multiple departments, and autonomous analysis all need completely different designs, even within the same company. Compares all three against real scenarios.


  • Foundry Data Pipelines: Pipeline Builder vs. Code Repository

    Foundry Data Pipelines: Pipeline Builder vs. Code Repository
    Summary — In Foundry, you can build a data pipeline two ways: the drag-and-drop Pipeline Builder, or the code-based Code Repository. Pipeline Builder is a good fit for quickly assembling simple transforms and joins; Code Repository is the right call once you need complex logic, or team-wide code review and version control. Either way, the […]

  • AI Agent Concepts, Hands-On: Build a Budget Summary App

    AI Agent Concepts, Hands-On: Build a Budget Summary App
    Summary — Reading about AI agents, prompt/context engineering, harness engineering, and agentic engineering only gets you so far without hands-on practice. This article builds a simple “budget summary app” together, walking through all four concepts step by step. Instead of real screenshots, each step includes the exact example prompts you’d type and example responses AI […]

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