Build, Run, Control AI. As Intended.

The Control Plane for Real-World AI

One platform to create, coordinate, govern, and optimize AI across the enterprise, aligned with business goals and intent.

From Enterprise Intent to Trusted Execution

01
Initial Idea
02
Articulate Intent
03
Specifications
04
UI Design
05
Test Cases & Scripts
06
Code Generation
07
Verification
08
Deploy
True to Intent
The Problem

Enterprises lack intent fidelity.

AI has created autonomous execution across the stack — without intelligent operational control. The bottleneck is no longer "can AI do the work?" It's "can enterprises trust what AI does?"

01

AI is reshaping operations

AI now autonomously writes code, generates workflows, modifies infrastructure, makes operational decisions, and coordinates agents.

02

Systems outpace control

Fragmented, undocumented systems evolve faster than the enterprise's ability to comprehend them — with no visibility, traceability, or accountability.

03

Operational control is missing

Without intelligent oversight, no one can verify that AI code, decisions, and outputs actually align with business intent.

04

IntentR closes the gap

The AI control plane that understands ecosystems, preserves intent, governs execution, and coordinates humans and AI safely.

AI agents fixate on coding — a sliver of the lifecycle. Without precise specs, AI executes the first (often wrong) plan it generates. IntentR governs the full lifecycle: ideation, specs, coding, validation, and deployment — across new, legacy, and third-party systems.

The Missing Layer

The required foundational infrastructure in the AI stack.

Incumbents own systems of execution. IntentR owns the system of operational control — sitting above every system in use, AI-led and legacy, ensuring they work together as intended.

IntentR — AI Control Plane

Understand · Coordinate · Govern · Operationalize

The missing layer

AI Coding & Model Layer

Copilot, Cursor, Claude, OpenAI — generates code and outputs

Execution

Data & AI Platforms

Databricks, Snowflake, Palantir — organizes data and models

Execution

Cloud Infrastructure

AWS, Azure, Google Cloud — hosts systems

Execution
Understand Coordinate Govern Operationalize

The Missing Layer Between AI and Business Outcomes

The Solution & Why We Are Different

Built on operational cognition — not generic AI.

"Why can't Microsoft, OpenAI, or Palantir just build this?" Because IntentR is built entirely on operational knowledge: understanding how entire AI ecosystems actually work in the real world, and whether they are doing what the business actually intended.

Key Differentiators

Semantic Reverse Engineering

Reconstructs undocumented legacy systems from the ground up, turning opaque operations into clear, executable models — across mainframes, cloud stacks, and industrial SCADA environments.

Intent Modeling

Preserves overarching business and mission intent, ensuring AI actions align with strategic goals — not just code fixes. Execution reflects what the business actually wants.

Cross-System Coordination

Operates fluidly across legacy mainframes, modern cloud stacks, and industrial environments.

Execution Governance

Deterministic traceability, rigid policy enforcement, and absolute human-in-the-loop control.

Operational Memory

Continuously learns system behaviors, improving autonomous performance over time.

"Incumbents own Systems of Execution. We own the System of Operational Control."

Nobody owns this new and necessary layer to manage AI-led operations. IntentR will.

Operational Intelligence

Continuously understands, governs, and predicts across your ecosystem.

Powered by semantic reverse engineering and intent modeling, the IntentR control plane generates operational intelligence in four dimensions.

1

Ecosystem Awareness

Cross-system context

  • Dependency drift detected automatically
  • Runtime state modeled continuously
  • Ecosystem relationships mapped end-to-end
2

Operational Risk Intelligence

Cascading risk prediction

  • Dependency conflicts detected before they cascade
  • Execution risk forecasted ahead of deployment
  • Remediation generated automatically
3

Predictive Intelligence

Opportunity + forecasting

  • Workflow optimizations identified proactively
  • 2x cost-reduction potential surfaced
  • Annual savings projected per workflow
4

Governed Execution

Policy compliance

  • AI deployments validated against policy
  • Human approvals enforced at every gate
  • Safe rollback always available
Proven, Not Promised

Already operating inside mission-critical systems.

Deployed across defense, intelligence, critical infrastructure, and enterprise environments — with validated, measurable results.

4–6h → 2min
Satellite image analysis processing time — national security deployment
2d → <30s
High-value target risk analysis, with <15% false-positive rate
95%+
Extraction accuracy on complex multilingual documents, ~70% less engineering effort
<4 hrs
To generate 4 new SCADA cyber capabilities; 36 vulnerabilities identified

Defense & National Security

Satellite Image Analysis

Processing reduced from 4–6 hours to ~2 minutes. Detection accuracy improved 15% with 50% less training.

Legacy SCADA Modernization

Reconstructed undocumented mission-critical infrastructure, enabling safe modernization without disruption.

Mesh Networks in Denied Environments

Resilient, off-grid communications operating in degraded and disconnected conditions.

Critical Infrastructure & Cyber

SCADA Cyber Analysis

36 vulnerabilities identified (4 critical). New analysis capabilities generated within 4 hours of development.

High-Value Target Risk Analytics

Analysis time cut from 2 days to under 30 seconds with a sub-15% false-positive rate.

Power Utility AI System

Interactive predictive analytics integrating 5 power utility systems — built in under 24 hours.

Enterprise & Data Systems

Complex Document Processing

95%+ extraction accuracy on multilingual PDFs while reducing engineering effort by ~70%.

Full-Platform Development

Design agency expanded from UX/UI into full platform development using IntentR — 2x revenue impact.

Enterprise Asset Management

Teaming agreements in place to deliver governed AI for large-scale government asset systems.

Market Opportunity

A multi-billion dollar layer nobody owns. Yet.

At the intersection of three massive markets.

As AI execution scales, the AI control plane becomes non-optional infrastructure — embedded deep in mission-critical operations, with high switching costs and long-term retention.

IntentR is an AI-powered software platform that enables organizations to build, operate, and govern intelligent systems while ensuring AI actions remain aligned with enterprise intent.

Table comparing eras: manufacturing led to ERP, internet to CRM, cloud to DevOps, and AI to the AI Control Plane

Similar to how the internet created the need for CRM software, AI is creating the urgent need for an AI Control Plane.

The Team

Built by operators of mission-critical systems.

Deep expertise across defense and intelligence, cybersecurity, industrial systems, autonomous AI, enterprise platforms, and critical infrastructure.

James Reynolds

James Reynolds

Chief Executive Officer
  • 30+ years platform engineering
  • 20 years in AI, with patents
  • Global technology leadership
  • Mission-critical systems
Bill Rector

Bill Rector

Chief Operating Officer
  • CIA Senior Intelligence Service
  • Operational leadership
  • Government & intelligence relationships
Shannon Bruffy

Shannon Bruffy

Chief Marketing Officer
  • Marketing Leadership – Amazon, Prime Video, Bloomberg
  • Scaled B2B Marketplaces Internationally

10

Core team members today

50–100

Cleared, specialized engineers available for rapid deployment

20+ yrs

Average experience, with active security clearances

AI tools write code.
IntentR makes it work as intended.

The transformative control plane making real-world AI systems operational, deployable, and trusted.