Operational�Intelligence�Revolution��Kevin Wise�Lead Solution Architect

What would it mean for your�organization if every decision were grounded in a single, trusted model of reality?

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The intellectual progression connecting early 20th-century philosophy�of language to the foundational ontological framework of Palantir.

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Ontology: The “shared language” that maps raw data to meaning

The architecture of meaning is a shared business grammar that every team, application, and AI model in your enterprise speaks fluently.

Measurable Outcomes (Theory to Reality, accelerated)

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Organizations adopting governed AI will permanently change their cost structures�faster than competitors can even diagnose the shift.

Objective: Expose the reality using an enterprise ontology

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The ontology maps the relationships, actions and dependencies among�objects to power a highly dynamic digital twin of the enterprise.

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This reality is the source of truth, free of fragmentation.

Disconnected Data

Database

Legacy Systems

Data warehouse

Object Storage

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Foundry has a full suite of integrated capabilities to power your architecture.

Modular

Combine components to build your data and operations platform of tomorrow.

Interoperable

Leverage existing data platforms, analytics tools, and governance paradigms.

Adaptive

Native tooling means your team can utilize new capabilities to meet changing needs.

PLATFORM THEMES

→ Application Building

With Foundry teams can self-serve, creating read-write applications and running simulations as needed

→ Data Science + Modeling

Enable full-stack data science. Foundry provides an integrated environment to develop, test and operationalize models.

→ Business Intelligence + Analytics

Foundry empowers users of all technical abilities to manipulate, analyze and act on data via intuitive, interactive applications.

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→ Data Integration

Foundry accelerates every aspect of pipelining with built-in automation, while safeguarding data integrity across collaboration.

→ Digital Twin

Beyond a data model, Foundry maps actions and relationships to form an interactive model of the enterprise,

Foundry is a suite of�modular, interoperable software building blocks�to accelerate your�ability to build.

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Integrated security & governance

Managed cloud infrastructure (Apollo)

Fully API-driven service mesh

SAML 2.0 Auth (SSO)

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Connectors

No-code

pipelines

Batch &

Streaming

Data Lineage

Data Health

Metadata Management

Data & Model Catalog

Semantic Data Layer

Actions Layer for API Building

Access Patterns: HDFS, REST, JDBC/ODBC

Indexed Search

Real-Time Analytics

Dashboard Building

Drill-down

Visualization

Model Evaluation

Model Deployment

Live Feedback

What-if Simulation

Pro-Code Dev

External Writeback

Low / No-Code

Decision Capture

^{Model Building}

Data Science & Modeling

BI & Analytics

Digital Twin/Ontology

Data Integration

^{Model Monitoring}

Application Building

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Hyperscaler components

Point solutions

Foundry offers the best of ‘build’ and ‘buy’ – enabling you to build better and offering flexibility for your evolving data strategy

Case Study:

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Array Technologies – Solar Energy at the Speed of Decision

Array Technologies is a leading US manufacturer of solar tracking systems for utility-scale solar projects

They compete on every major project in America — typically shortlisted alongside two�other providers — and serve a design chain of Developers and EPCs (Engineering, �Procurement & Construction firms) who rely on Array to deliver optimized �solar tracker designs and quotes.

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The Operational Reality

1,500 opportunities per year in the US market alone

14 design iterations per project (10 at the EPC level + 4 at the Developer level), with ~10 revisions per customer

1,600 engineering hours per project consumed across 40 total iterations at ~40 hours each

Average deal size of $28–30M with 28–31% margins — every deal won or lost carries massive financial weight

Projects are known 3–5 years in advance — location, terrain, corrosion parameters, weather, building codes — yet this data sits unused across siloed systems

The core question: What would it mean if Array could transform this fragmented, manual design process into a single, living model of every project — and turn weeks of iteration into hours of decisive, consultative engagement?

Nearly 2x as slow as�their primary competitor

The Problem Statement: You are the best, but you are too slow.

Array leads in product quality. Array leads in price competitiveness. Array's engineering talent is world-class. ��But Array is positioned as #3 — because in the design-to-quote race, they finish last.

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The Burning Platform

80–90% manual engineering process — siloed, standalone, no memory of prior iterations, no "what-if" capability, no cross-project learning

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5–10% assumption errors on intake forms — each error triggers a full rework cycle costing ~5 additional days

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No differentiation between budgetary and final quotes — the same labor-intensive process runs for every single revision

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25–30% win rate — directly correlated to slow responsiveness and the inability to iterate consultatively

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Array takes too long.�

There were a number of deals I could not get out the door in December.�

Our design was completely non-competitive, fortunately they gave us an opportunity to requote.

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Their data exists across 12+ systems. But fragmented architectures have created a profound "conceptual alienation" — the systems don't talk, the data doesn't flow, and by the time a quote surfaces, the window for action has closed.

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The problem is not data. The problem is meaning.

Actual Customer Feedback

From Reactive #3 to Consultative Market Leader

With Rackspace and Palantir, Array doesn't just get faster. Array fundamentally changes how it sells.

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Three-Stage Operational Intelligence Transformation

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Competitive Parity Plus

Palantir's Ontology maps every Project, EPC, Design Parameter, Module Spec, and Cost Driver as living objects

Relationships between terrain data, corrosion parameters, weather patterns, and building codes are explicitly modeled and queryable in real-time

AI agents pull data automatically from multiple sources, eliminating the 5–10% assumption errors that currently trigger full rework cycles

Automated hand-offs and cost-inclusive simulations compress cycle time from 9 days to 3–4 days — achieving competitive parity

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Competitive Advantage (The North Star)

The digital twin enables optionality quoting — instead of back-and-forth, Array delivers multiple optimized design alternatives upfront in 2 days

EPCs see trade-offs between cost, terrain, module selection, and performance — this is consultative selling not commodity chatbots

Self-serve tools let Developers and EPCs explore scenarios independently — upscaling Array's workforce meaning more projects at higher quality

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The Permanent Acceleration

With 3–5 years of project data visible in advance, Array's ontology becomes a self-reinforcing competitive moat�

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better data → sharper models → faster designs → more wins

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�Array transforms from a reactive component supplier into a proactive thought leader that EPCs and Developers think of first

Win rate improvement: +10.5% to +11.5% 3-Year NPV: $137M – $245M | ROI: 25x – 45x

Win rate improvement: +5.5% to +7.5% 3-Year NPV: $72M – $98M | ROI: 16x – 22x

Why This Only Works with Rackspace + Palantir��Rackspace delivers the consulting-driven business transformation, domain expertise, and managed services that turn platform capability into sustainable operational advantage��Together: faster time to value, lower compliance risk, stronger ROI, and a permanently reduced operational burden through continuous monitoring, management, and optimization

Array went from losing deals because “they take too long” to winning more business through faster, smarter, consultative quoting – powered by Palantir and Rackspace’s AI-first delivery model

Why Rackspace

The Truth: AI Investments are failing

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Why AI investments fail

No clear use case

Organizations are driven to adopt AI by competitive pressure rather than targeting specific business problems

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Unable to prove impact

Attribution complexity makes it impossible to isolate AI's contribution from other concurrent initiatives

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Intangible benefits

AI delivers outcomes that matter but are difficult to quantify financially using traditional metrics

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Build faster with interoperable software that unifies data, insights, and actions

Modular Software

Choose modules to power your tech stack – from data integration to advanced analytics to application building.

Operations-Focused

Build AI-capable workflows to connect crucial business functions and power closed-loop decision-making.

Speed to Value

Automate years of implementation work – supercharging your existing data platforms and analytics systems within weeks.

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Why Rackspace + Palantir: �Better together

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Rackspace

Palantir

Rackspace-powered Palantir implementation journey

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Use case 2

Use case 3

Use case 4+

= FDE(s) deployed

Deliverables

• Identify and validate areas with the biggest financial impact
• Understand state of data architecture
• Assess executive sponsorship

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Deliverables

• Prioritized and documented top use cases
• Data readiness assessment report
• Technical requirements and integration points

Deliverables

• Demonstrate proof of value
• Financial business case
• Go/no-go analysis on production implementation

Deliverables

• Production use case
• ROI validation report
• Next use case roadmap
• Operational documentation

Discovery

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Day 1

Workshop

(speedrun)

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Day 2

AgentCamp

(bootcamp)

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Week 2 (5+ days)

Use Case

Implementation�

Week 3 (2+ months)

Future use case engagements

Ingredients of accelerated Operational Intelligence

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Rapid Operational Intelligence�at scale

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A single model of reality isn't just about better data; it’s about a common language.��When we all see the same truth, we stop arguing about what happened and start deciding what happens next.��Let’s build that reality together.

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