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Architecting the Automotive Intelligence Era.
Auto Agentic is not building another automotive technology company. We are building the intelligence infrastructure that the automotive industry will run on — coordinated across dealerships, dealer groups, and OEM ecosystems.
Why Auto Agentic exists.
Automotive is not lacking software. It is lacking intelligence architecture.
Intelligence does not emerge from accumulating tools. It emerges from how systems, data, workflows, and organizations are designed to work together.
Over the last decade, the automotive industry has moved aggressively toward AI tools, point automation, and "intelligent" features. The result has not been transformation. It has been coordination debt — more systems, more reconciliation, more friction at the seams where intelligence was supposed to compound.
- We built the Automotive Intelligence Pyramid™ to define how intelligence actually matures inside an automotive organization.
- We built an agentic intelligence architecture to make the higher levels of the Pyramid operationally possible.
- We formed Auto Agentic to guide the industry from fragmented automation to interconnected, compounding intelligence.
How the architecture actually works.
Auto Agentic's Intelligence Foundation is four layers, federated at the data layer and progressively normalized above it. This is the accurate model technical reviewers will ask about. In buyer-facing materials we compress it for communication speed; for investors, the honest structure is below.
Rooftop Data Lake
One per rooftop. Raw operational data from connected systems. Rooftop owns the data — it is not moved, mirrored, or centralized above this layer.
Rooftop Knowledge Hub
One per rooftop. Normalizes that rooftop's data into standard schemas. Powers day-to-day workflows at the rooftop. Each rooftop has a coherent, unified view of its own operations.
Group Knowledge Hub
One for the group. Normalizes across the Rooftop Knowledge Hubs. The meta-normalization layer that produces cross-rooftop benchmarking, pattern propagation, and emergent group-level analytics — without commingling the raw data.
Agentic AI Layer
The orchestration layer above the Group Knowledge Hub. Routes agents to the rooftop or group scope depending on the workflow. This is where the 100+ agents operate.
This structure compounds over time in two dimensions. Per rooftop: every month of operation deepens that rooftop's pattern library inside its own data lake and rooftop Knowledge Hub. Group-wide: every month of operation deepens the cross-rooftop normalized view at the Group Knowledge Hub — and that layer sharpens faster, because patterns from Rooftop A inform Rooftops B through Z via the Group Knowledge Hub. A competitor starting two years late cannot buy either level. Capital cannot compress operational learning time at the rooftop level, and it cannot retroactively assemble a cross-rooftop pattern library that has not been accumulated.
The market opportunity.
Automotive is one of the fastest-growing enterprise technology sectors globally.
Global automotive AI and intelligence software market, projected through 2030.
North American automotive-focused AI market — the geography where Auto Agentic operates.
Dealer groups, enterprise platforms, and OEM intelligence systems reachable in North America.
Franchise dealerships in North America
OEMs actively investing in AI infrastructure
Automotive AI market projected growth
75% Canadian-owned. Global by design.
Auto Agentic is headquartered in Canada — the birthplace of modern AI — giving us foundational access to the world's deepest concentration of deep-learning research and talent.
Where modern AI was born
The deep-learning revolution that powers today's AI was born in Toronto and Montreal. Geoffrey Hinton (University of Toronto, Vector Institute) and Yoshua Bengio (Université de Montréal, Mila) — both Turing Award winners, the highest honor in computer science — built the foundational architectures of modern AI. Canada invested $1.5 billion in AI research a decade before AI became commercially viable, establishing the intellectual substrate the global industry now depends on.
A global AI platform, built from Canada
Meta's Chief AI Scientist Yann LeCun, OpenAI's research leadership, and many of the founding figures at today's AI giants trained under Hinton, Bengio, or at institutions they built. Canada produces a disproportionate share of the world's top AI talent. Auto Agentic is built on that talent network, applied to the most operationally complex industry on earth.
Turing Award winners for deep learning are Canadian
Canada's historical investment in AI research
Auto Agentic Canadian ownership
Vector Institute founded
Our strategy.
Auto Agentic is executing a deliberate five-year strategy.
Genesis
Architecture, framework, and enterprise foundation established. Core agentic intelligence stack built. Stress-tested in proofs of concept.
Foundation (Current)
Limited strategic partnerships to prove, pressure-test, and codify foundational playbooks. Founding Partner cohort of five qualifying dealer groups. Case studies generated, not promised.
Activation
Industry-scaling deployment. Intelligence enablement across multi-location dealer groups, OEM environments, and agency partners. Proven architecture, repeatable methods, demonstrated outcomes.
Scale
Automotive intelligence infrastructure becomes foundational — the operating layer the industry runs on. Connected automotive ecosystem. Continuous intelligence evolution.
We are not optimizing for consumer scale. We are optimizing for coherence of architecture — because in intelligence systems, early-stage decisions compound for decades.
Leadership team.
Four co-founders with 100+ combined years across automotive, enterprise AI, and organizational transformation.
Barry Hillier
CEO
Strategy, Brand, and Growth Architecture. 25+ years scaling businesses across automotive, SaaS, and emerging tech. Technology entrepreneur and intelligence-architecture strategist working at the front edge of the shift from the Transactional Age to the Intelligence Age. Co-founder of eight ventures across automotive systems, applied AI, digital platforms, and consumer brands. Creator and producer of the Auto Intelligence Podcast.
Bill Playford
Chief Growth Officer
Operations, Analytics, and Change. 20+ years in dealership operations. Has worked with more than 1,200 dealerships across the United States and Canada. Operator-level understanding of how dealer groups actually run and what slows them down.
Michael Carrick
CTO
Enterprise Architecture and Agentic Systems. 25+ years of enterprise architecture in financial services and critical infrastructure. Designs and oversees the Intelligence Foundation, Knowledge Hub, and agentic orchestration layer.
Karla Congson
Chief AI Strategist
AI Strategy, Governance, and Transformation. 25+ years in enterprise AI and digital transformation. Leads AI strategy, governance, and agentic system design across the Auto Agentic platform.
Our ideal investor profile.
We seek capital partners aligned with building long-term intelligence infrastructure — not capital seeking accelerated distribution.
We partner best with investors who bring:
- Experience in platform infrastructure or complex, multi-stakeholder coordination systems
- Comfort with long-horizon value creation — five to ten years, not two
- Appreciation for the difference between platform velocity and product velocity
- Understanding of narrative dominance as a category-creation strategy
- Respect for operator insight as a real input to architecture decisions
- Alignment with diagnostic, thesis-led company building
Why we are intentionally selective:
- Our architecture defines the ceiling of the capital we deploy against it
- Our partnership model and incentive structure must match the long-arc payoff of infrastructure businesses
- Our early decisions determine what becomes possible over ten years
- Our capital partners participate in shaping an industry foundation, not in selling a product
We value capital, but we prioritize judgment.
How investors engage with Auto Agentic.
Strategic investors in Auto Agentic are engaged partners, not distant LPs.
Intelligence platform evolution
Participate in defining the capability roadmap of the agentic architecture as it scales across the industry.
Automotive strategy evolution
Bring perspective on where automotive and mobility markets are moving, and how Auto Agentic's platform positions against that movement.
Governance and ethics of foundation
Engage on how agentic systems at industry scale should be governed — data sovereignty, model policy, human-in-the-loop standards.
Category definition and narrative leadership
Help shape how the category of automotive intelligence infrastructure is defined, understood, and adopted.
We are building the operating layer for automotive intelligence. That benefits from thoughtful, strategy-aligned capital.
The opportunity.
Automotive is one of the world's largest, most operationally complex industries.
As automotive moves from point tools to intelligence systems, what the market does not need is more point tools. What the market needs is architecture.
Auto Agentic is building these foundations. Only a handful of organizations are positioned — intellectually, operationally, and geographically — to define how intelligence actually operates inside the automotive industry. Our market experience and our position in Canada's AI ecosystem give us a seat at that table for the next decade.
Investor inquiries.
We welcome conversations with investors who share a long-term view of architecting the Intelligence Transformation — and who understand what it takes to build compounding infrastructure rather than ship a product.
In the discussion, please bring:
- Respect for the deliberate pace of foundational architecture
- Time for a thorough strategic conversation
- An understanding of intelligence architecture as a category, not a feature set
- Experience with platform or ecosystem-driven businesses at any stage
If there is alignment, we welcome the conversation.