OCTION LABS

Sovereign AI for regulated Canada.

We build the AI stack that public-sector and regulated buyers are legally allowed to use: hardware we own, data they keep, compliance built in. Phase 0 is live.

Oction AgencyConfidential

OCTION LABS

THE THESIS

We own the three things every other AI vendor only rents: the hardware, the data lifecycle, and the compliance framework.

Regulated and public-sector clients cannot legally hand citizen and patient data to OpenAI, Anthropic, or a US cloud. They still need AI. We are the only model built to sell to them on infrastructure we control, in province, with an audit trail.

00000001 · 01/15

OCTION LABS

THE PROBLEM

Regulated industries want AI and cannot legally buy what is on the market.

Municipal governmentprovincial data-sovereignty rules restrict cloud LLMs for citizen data.
HealthcarePHIPA, HIA, Law 25, and PIPEDA push patient data toward local processing; the US CLOUD Act makes cross-border cloud a documented risk.
Finance and legalSOC 2 and client-confidentiality rules block general SaaS AI tools.
Public safetyNIST 800-53 mandates controlled supply chains and audit trails.

The gap: every vendor pitches "secure." None can prove sovereign infrastructure. Buyers want AI but cannot legally buy what is available.

00000010 · 02/15

OCTION LABS

WHAT WE DO

Three models on one vertically integrated stack. Each makes the next more defensible.

Phase 0, Sovereign Compute Pilot (live): grant-eligible proof of concept. Portable compute deployed on client sites to validate data sovereignty, a NIST 800-53 baseline, and the procurement path before production scale.
Model 1, Sovereign AI Deployment (operating): bespoke software plus managed on-premise infrastructure for regulated clients. We own the hardware. Clients own the data. Compliance is built in, not bolted on.
Model 2, Proprietary Data Assets (scaling): anonymized, permissioned operational data from Model 1 becomes licensable training material and enrichment APIs.
Model 3, Sovereign Compute Hubs (government-targeted): inference and HPC clusters for government co-location, on multi-year contracts. Physical ownership of the stack is the switching cost.

One line: we build the only AI stack regulated buyers are legally allowed to use.

00000011 · 03/15

OCTION LABS

WHY NOW

Three forces open a 24 to 36 month window.

Regulatory urgencyNIST 800-53 Rev. 5, provincial AI procurement rules, and EU AI Act spillover into Canadian standards are forcing buyers to act.
Sovereignty pressurefederal strategy increasingly favors domestic AI scale-ups; public-sector buyers are actively moving off pure US cloud dependence.
Talent arbitrageCalgary and Edmonton AI ecosystems (Amii, University of Alberta) are under-recruited relative to Toronto and Vancouver.

Miss the window and incumbents (Deloitte, CGI, IBM) fill it with overpriced, underperforming solutions.

Note: prior versions cited a specific power-draw multiplier for the compute hardware. We removed it pending a measured benchmark rather than ship an unverifiable claim.

00000100 · 04/15

OCTION LABS05 / 15

MARKET OPPORTUNITY

We sit at the intersection of four segments, each with defined buyers and procurement paths.

Canadian municipal AI services

NotesPredictable procurement, defined compliance

Sizing statusInternal estimate

Regulated enterprise AI (health, finance, legal)

NotesHigh contract value, slow but sticky

Sizing statusInternal estimate

Sovereign data licensing

NotesProprietary asset layer from Model 1

Sizing statusInternal estimate

Government compute and grants

NotesGovernment-funded infrastructure

Sizing statusInternal estimate

OCTION LABS

TRACTION

Built with no outside capital. This is a deployed systems company, not a science project.

Phase 0 liveCyntech Group geotechnical knowledge assistant running on Oction's on-premise stack in a regulated Canadian enterprise.
Autonomous agent mesh operating on dedicated hardware around the clock (Julian, Lucius, Atlas, and specialist agents).
30,000+ indexed knowledge chunks across a triple-layer RAG/CAG/KAG memory system with hybrid search.
Live infrastructurelocal LLM proxy, memory API, vector store, and cache, all healthy.
NIST 800-53 security framework implemented, documented, and audit-ready.
Active buyer pipelinemultiple Alberta municipal conversations and two systems-integrator relationships at pilot stage.

Honest framing: conversations and pilots are in progress; no production enterprise contract is signed yet. We do not claim revenue we do not have.

00000110 · 06/15

OCTION LABS

THE DATA FLYWHEEL

Every Model 1 client makes Model 2 more valuable. Margins expand as we scale.

Deployeach client generates anonymized, permissioned operational data.
Encodepatterns become reusable knowledge graphs, templates, and playbooks.
Modularizeproven infrastructure configs become repeatable deployment modules.
Licenseanonymized datasets and tuned weights become proprietary, licensable assets.

Year 1 looks like services. Year 3 looks like software plus data. The flywheel is the path from project margins to platform margins.

00000111 · 07/15

OCTION LABS08 / 15

COMPETITIVE LANDSCAPE

Compliance fluency times hardware control times data ownership equals no direct competitor.

Deloitte / CGI / Accenture

Their weaknessHigh hourly labor, long sales cycles

Our advantageFixed-price deliverables, short pilots

OpenAI / Anthropic / US cloud

Their weaknessCannot sign in-province data-residency on owned hardware

Our advantageHardware we own, in province, auditable

Local MSPs

Their weaknessNo AI depth, no knowledge graph

Our advantagePurpose-built agent mesh plus memory stack

Internal IT teams

Their weaknessNo budget, talent, or compliance fluency

Our advantageWe are the outsourced sovereign-AI department

OCTION LABS

TWO VERTICALS, ONE STACK

The same sovereign stack serves municipal government and healthcare. Healthcare is the higher-value, higher-defensibility wedge.

Municipalpredictable procurement, defined compliance, faster first contracts. The proving ground.
Healthcarelarger contracts, deeper switching costs, strong non-dilutive funding (Infoway, Vector, CIHR, IRAP), and public outcome proof (CHARTWatch cut unanticipated in-hospital deaths 26%, peer-reviewed in CMAJ, Sept 2024).
The healthcare partnership/pilot motion runs on a separate deck. The investor story is that one stack addresses both, de-risking concentration in any single segment.

Sources: CMAJ / Unity Health Toronto (2024).

00001001 · 09/15

OCTION LABS10 / 15

TEAM

A systems and infrastructure company run by operators, multiplied by an always-on agent staff.

Brandon Gill

RoleCo-CEO, Revenue and Government Relations

OwnsSales, partnerships, capital strategy

Bailey Rhodes

RoleCo-Founder, Owner

OwnsStrategic oversight, capital deployment

MJ Dewji

RoleCo-Founder / COO

OwnsOperations, sales execution, partnerships

Julian Pierce

RoleCo-CEO, Systems and Infrastructure

OwnsAgent mesh, security, on-premise deployment

Lucius Fox

RoleCo-CEO, Operations Intelligence

OwnsMemory systems, research, workflow design

Atlas

RoleSecurity and Forensics

OwnsNIST 800-53, audit trails, threat detection

OCTION LABS

WHY WE WIN - THE MOAT

The moat is structural, not feature-based.

Hardware we own becomes the client's switching cost; the compute does not leave.
Compliance fluency (NIST 800-53, provincial health and privacy law) is a sales gate competitors cannot fake.
The data flywheel compoundseach deployment makes the next cheaper to deliver and the data layer more valuable.
Canadian-built and in-province is a procurement requirement, not a marketing line, for our buyers.

Cloud AI vendors cannot follow us here without abandoning the cloud economics that define them.

00001011 · 11/15

OCTION LABS

THE BET

Regulated AI is not a feature. It is a market, and it is up for grabs in the next 24 months.

We own the hardware. We own the data lifecycle. We own the compliance framework. Every competitor rents one of the three.

The companies that solve regulated, sovereign AI in the next two years will define the next decade of enterprise and public-sector infrastructure in Canada. We intend to be one of them.

00001100 · 12/15

OCTION LABS

THE ASK

$25M for 8 to 10% equity. $250M to $312.5M post-money.

This round turns Oction from a services-led systems company into a sovereign AI infrastructure platform. Capital deploys against three proven vectors:

1. Production deployments with municipal and regulated-enterprise clients.

2. Proprietary data assets built from client operations.

3. Grant-aligned sovereign compute hubs that lower cost and deepen the moat.

Funding alignment: sized to match Canadian sovereign-AI and innovation co-investment timelines (ISED, NRC, Alberta Innovates).

Note: valuation and round terms reflect founder positioning; the post-money range is a target, not a closed instrument.

00001101 · 13/15

OCTION LABS

USE OF FUNDS

Capital is allocated to scale deployments, build the data layer, and hold a strategic reserve.

Core ops and team expansion

Allocation60%

Amount$15M

PurposeRunway to scale deployments, compliance, field engineering

Data acquisition and enrichment

Allocation20%

Amount$5M

PurposeProprietary data assets for Model 2 licensing

M&A and contingency reserve

Allocation20%

Amount$5M

PurposeStrategic tuck-ins, grant match, reserve

Target runway: 24 to 30 months. ARR and break-even targets are founder projections, not commitments.

00001110 · 14/15

OCTION LABS

CONTACT AND APPENDIX

Decision-ready. The ask is $25M at 8 to 10% equity.

Brandon Gill: brandon@octionlabs.com

Bailey Rhodes: bailey@octionlabs.com

Julian Pierce: julian@octionlabs.com

Lucius Fox: lucius@octionlabs.com

Appendix available on request: NIST 800-53 control mapping; sovereign compute hardware specifications; agent mesh architecture; knowledge system technical overview; municipal procurement playbook; systems-integrator partnership letters; ISED / NRC / Alberta Innovates funding roadmap.

00001111 · 15/15