Palantir Intelligence Quick Start Guide

1-2-3 Framework for Strategic Application

Purpose: Rapidly operationalize Palantir strategic insights for CODITECT product development

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1️⃣ UNDERSTAND — The Palantir Model

The Core Insight (60 seconds)

Palantir proved that AI value = Ontology + Operations + Autonomy:

Raw Data → Ontology (semantics) → AI Workflows → Autonomous Actions → Measurable ROI

They didn't build better models. They built better infrastructure for models to operate in.

The Three Pillars (5 minutes)

Pillar 1: Ontology — The Semantic Foundation

• Digital twin of the organization
• Objects, properties, relationships mirror real-world entities
• AI understands context, not just data
• Example: "Customer" isn't a row—it's linked to orders, payments, communications, risk scores

Pillar 2: AIP — The AI Orchestration Layer

• Run LLMs on private networks with full control
• AIP Logic: Build AI-powered functions
• AIP Agent Studio: Create autonomous agents
• AIP Evals: Measure AI performance in production

Pillar 3: Apollo — The Deployment Fabric

• Deploy anywhere: cloud, on-prem, edge, classified
• Continuous delivery for mission-critical systems
• Enables "sovereign AI" for government clients

The Business Model (2 minutes)

Component	What It Does	Revenue Driver
Gotham	Defense/intelligence operations	Government ARR
Foundry	Commercial data operations	Commercial ARR
AIP	AI integration layer	Growth multiplier
Apollo	Deployment automation	Stickiness + margins

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2️⃣ EXTRACT — Patterns for CODITECT

Pattern 1: Ontology-First Architecture

Palantir's Approach:

Disparate Data Sources
         ↓
    [Integration Layer]
         ↓
    [Ontology Layer] ← Business Objects, Links, Actions
         ↓
    [Application Layer] ← Workshop, Quiver, Custom Apps
         ↓
    [AI Layer] ← AIP for LLM orchestration

CODITECT Application:

Healthcare/Financial Data Sources
         ↓
    [CODITECT Integration]
         ↓
    [Domain Ontology] ← Patients, Claims, Providers, Regulations
         ↓
    [Workflow Automation] ← Compliance, Documentation, Approvals
         ↓
    [AI Agents] ← Specialized for regulated industries

Pattern 2: The Bootcamp GTM Model

How Palantir Does It:

1. Invite prospect to 5-day intensive
2. Connect their actual data to Ontology
3. Build production-ready AI workflows
4. Demonstrate measurable value
5. Convert to enterprise contract

CODITECT Adaptation:

Day	Palantir Focus	CODITECT Healthcare Focus
1	Data connection	EHR/claims integration
2	Ontology mapping	Patient/provider/encounter modeling
3	Workflow building	Documentation automation
4	AI integration	Compliance validation agents
5	Value demonstration	ROI: hours saved × hourly cost

Target Outcome: "20x ROI in 20 Days" → compress to "2x ROI in 2 Days" bootcamp demo

Pattern 3: Agentic AI Architecture

Palantir's 2026 Direction:

• "Agentic AI Hives" — autonomous agents for supply chain
• From "decision-support" to "decision-execution"
• Humans set guardrails; agents execute within them

CODITECT Implementation:

# CODITECT Agent Pattern (inspired by Palantir)
class HealthcareComplianceAgent:
    """
    Autonomous agent operating within regulatory guardrails
    """
    
    def __init__(self, ontology: DomainOntology, regulations: List[Regulation]):
        self.ontology = ontology
        self.regulations = regulations
        self.audit_trail = AuditTrail()
    
    async def execute_workflow(self, trigger: WorkflowTrigger) -> WorkflowResult:
        # 1. Plan execution within guardrails
        plan = await self.plan(trigger, self.regulations)
        
        # 2. Execute with checkpoints
        for step in plan.steps:
            result = await self.execute_step(step)
            self.audit_trail.record(step, result)
            
            # Human checkpoint for high-risk decisions
            if step.requires_human_approval:
                await self.request_human_checkpoint(step, result)
        
        # 3. Return with full audit trail
        return WorkflowResult(
            outcome=plan.outcome,
            audit_trail=self.audit_trail,
            compliance_artifacts=self.generate_compliance_artifacts()
        )

Pattern 4: The "Load-Bearing" Principle

Karp's Insight:

AI pen tests your organization. It exposes what can actually bear the load.

CODITECT Application:

• Don't automate dysfunction — identify processes worth automating
• Surface hidden value — AI reveals where expertise actually resides
• Design for truth — workflows must reflect real operations

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3️⃣ IMPLEMENT — 30-Day Action Plan

Week 1: Foundation

Day	Action	Deliverable
1-2	Define CODITECT Ontology primitives	Object types for healthcare/financial
3-4	Map competitor patterns	Palantir vs. CODITECT feature matrix
5	Design bootcamp prototype	2-day healthcare automation demo

Key Question: What are the 10-15 core object types for CODITECT's domain ontology?

Week 2: Architecture

Day	Action	Deliverable
6-7	Design agent orchestration layer	Architecture diagram
8-9	Define compliance guardrails	Regulatory constraint model
10	Build deployment abstraction	Cloud/on-prem/hybrid support

Key Question: How does CODITECT achieve "Apollo-like" deployment flexibility?

Week 3: GTM Validation

Day	Action	Deliverable
11-12	Prototype bootcamp workflow	Interactive demo
13-14	Create ROI calculator	"Eliminates 60-90% repetitive work" validation
15	Test with target customer	Feedback loop

Key Question: Can we demonstrate measurable value in 2 days instead of 5?

Week 4: Competitive Positioning

Day	Action	Deliverable
16-17	Articulate differentiation	"Why CODITECT vs. Palantir" pitch
18-19	Build reference architecture	Published technical spec
20	Plan pilot program	First 3 customer targets

Key Question: What does CODITECT do better than Palantir for regulated industries?

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Quick Reference: Palantir Metrics to Track

Rule of 40 Framework

Rule of 40 = Revenue Growth Rate + Operating Margin

Palantir Q4 2025: 70% + 57% = 127% (extraordinary)
Typical "good" SaaS: 40%+
CODITECT Target: 60%+ (growth-focused)

Key Performance Indicators

Metric	Palantir Q4 2025	CODITECT Target
YoY Revenue Growth	70%	>50%
U.S. Commercial Growth	137%	>100%
Adjusted Operating Margin	57%	>30%
Net Dollar Retention	>120%	>115%
Bootcamp → Contract Conversion	~60%	>50%
Time to Value	5 days	2 days

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Appendix: Key Quotes for Reference

On AI and Jobs (Karp, Davos 2026)

"The revolution that's coming is going to expose the actual market value of what you're doing, whether we want it or not."

On Technical Workforce (Karp, Davos 2026)

"Vocational technicians are going to become more valuable. Those jobs are going to become more valuable."

On Value Delivery (Karp, Q4 2025)

"We deliver a high-value product. We don't want any BS about getting paid. We're not going to give you any BS about why our product didn't work."

On Product Strategy (Karp, Q4 2025)

"Build products that are so good that the competition stops competing."

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Next Steps

1. Read: CODITECT Impact Analysis for strategic implications
2. Review: System Design Document for Palantir architecture deep-dive
3. Execute: Deep Research Prompts for product development focus

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Quick Start Guide v1.0 — February 2026