Agent Foundry — Sovereign Agentic AI Infrastructure

Agents that survive production.

The infrastructure layer that turns a foundation model into a reliable, observable, governable agent. Built in Canada, on Canadian compute, under Canadian governance — with every action authorized, logged, and auditable.

25Production primitives

6Architectural layers

100%Canadian-owned & controlled

0Foreign dependencies in the critical path

01 — The Problem

The gap isn't intelligence. It's infrastructure.

Enterprise AI is at an inflection point. The models are capable — the engineering around them is not. Canadian organizations that need sovereign, auditable, production-grade agents now have a foundation model, but no application layer. The last mile of sovereignty is unclaimed territory. Agent Foundry fills it.

40%+

of agentic AI projects will be cancelled by 2027 — not because models fail, but because the engineering around them can't survive production. (Gartner)

88%

of AI proofs-of-concept never reach production. Demos are easy. Operations are hard. We build for operations.

02 — Architecture

Production-grade by construction, not by aspiration.

Most agentic frameworks are designed for demos and retrofitted for production. Agent Foundry was built the other way around: governance, observability, and auditability are architectural primitives — 25 of them, across six layers spanning the full agent lifecycle.

Continuity

Episode sealing · Continuity capsule · Temporal orientation · Memory with decay

Agents carry context across sessions without accumulating drift. Every interaction is grounded in verifiable source events.

Knowledge

Grounded knowledge graph · Memory bundles · Evidence attribution · Entity resolution

Durable, queryable knowledge that distinguishes verified facts from inferences. Every claim traces to its source.

Reasoning

Curiosity system · Epistemic critic · Drift monitor · Latent thoughts

Agents investigate open questions, challenge their own assumptions, and detect when their reasoning has shifted — with every shift logged.

Governance

Work docket · Audit trails · Publication policy · Capability schemas

Full observability into what the agent did, why, and what it was authorized to do. Every capability is declared in advance.

Behavioral Consistency

Persona framework · Voice specifications · Self-model · Affect modeling

Judgment that stays consistent and predictable over months and years. Behavioral identity is architectural and versioned — what you certified is what stays deployed.

Bounded Autonomy

Background cognition · Event-driven processing · Operator-approved outreach · Tick loop

Agents work between conversations — monitoring, investigating, preparing — inside explicitly declared authority boundaries. Scoped, revocable, fully logged.

03 — Why Not the Incumbents

The questions every evaluator asks.

Why not LangGraph, CrewAI, AutoGen?

Open-source frameworks are orchestration toolkits — the plumbing to build an agent. They don't give you continuity, evidence attribution, drift detection, declared-capability governance, or audit trails. Agent Foundry is the production layer they lack — and it can host agents built with them.

Why not Microsoft Copilot Studio or US hyperscaler platforms?

Sovereignty: a US-controlled platform is subject to foreign legal reach and cannot claim Canadian value-added content under the Buy Canadian Policy's 25% Canadian-content scoring. Agent Foundry can. Depth: hyperscalers optimize for breadth of demos, not audit-surviving traceability.

Why not Cohere's own platform?

Cohere is a partner, not a competitor. Agent Foundry runs on Cohere models and is deliberately model-agnostic — the same governance, continuity, and audit layer works across Cohere, open-weight models, or future frontier models. Any model, one governance standard, Canadian control.

04 — Sovereignty & Compliance

Sovereign by design. Auditable by default.

Designed for deployment under Canadian privacy law (PIPEDA and provincial equivalents) and emerging federal AI governance. A deployment-specific privacy impact assessment template ships with the platform.

Data residency

All state — memory, knowledge graphs, audit logs — resides on Canadian infrastructure, customer-controlled.

Purpose-bound memory

Agents retain what the deployment's data policy declares. Retention, decay, and deletion are enforced architecturally — not by prompt.

Evidence attribution

Every claim traces to a source event, supporting access, correction, and accountability obligations.

Human oversight

Capability schemas define what an agent may do; publication policies define what it may say externally. Every boundary crossing requires operator approval — and is logged.

Audit-ready

Full audit trails export in forms suitable for model-risk review, regulator examination, or ATIP requests.

FOCI-clean

Canadian-owned and controlled. Procurable under the Buy Canadian ICT strategic category, with 10% price preference and 25% Canadian-content scoring.

05 — The Pilot

Scoped. Measurable. Low-risk.

We're selecting lighthouse partners — Crown corporations, port authorities, and regulated institutions — for first deployments. The engagement is designed so your security, privacy, and procurement teams can say yes.

One workflow, 8–12 weeks

A single painful, well-bounded workflow in your organization, deployed on Canadian infrastructure. We pick the one with the clearest baseline and the most pain.

Metrics in writing, first

Cycle time, error rate, audit completeness, operator hours saved — agreed before we start, measured before and after.

Your governance, full access

Security, privacy, and model-risk teams get complete visibility into the audit layer from day one. If it doesn't survive your scrutiny, you keep the evaluation data and walk away.

Scale or walk away