AI-augmented enterprise strategy
Experiatech helps leadership teams examine more evidence, test more scenarios and operationalise decisions faster—while preserving traceability, human authority and architectural control.
Montreal · Canada and France · Regulated environments
Business outcomes, use-case portfolio, value and risk appetite
Capabilities, information, platforms and boundaries
Roles, knowledge, governance and delivery practices
Agents, controls, telemetry and evidence
Three ways to build strategic capacity
The offers strengthen different parts of the same decision system. Consulting applies the method, training transfers it and bounded agents increase operational capacity.
Capability map · target state · decision record · transition roadmap
Turn consequential decisions into governed execution.
Apply the Strategy Amplification Loop to AI strategy, target architecture, Azure transformation and Snowflake data-platform decisions.
Decision framework · governance charter · reference architecture · action plan
Build judgment that survives the next tool cycle.
Private programmes build the judgment and reusable methods teams need to frame, challenge and operationalise real decisions themselves.
Semantic understanding · credit governance · query performance
Increase capacity inside one named operational boundary.
Deployable Snowflake agents produce traceable evidence for operational decisions, with read-only defaults, explicit permissions and human approval for change.
Our thesis
Strategic leverage comes from examining more evidence, challenging more assumptions and converting decisions into owned artifacts. The model is only one component of that system.
“More evidence. More alternatives. Clearer authority.”
Snowflake launch suite
Identity · integration · Microsoft Foundry · evaluation · telemetry
Data products · semantics · governance · FinOps · operations
Strategy remains portable. Platform choices become explicit where identity, data residency, controls and operating responsibility matter.
What is this table, who owns it, where does it come from, and what depends on it?
Product detail →Which workloads are consuming credits, why, and who is accountable for the spend?
Product detail →Why is this workload slow, and what evidence supports the recommended change?
Product detail →Company-led, founder-backed
Experiatech is a Montreal-based enterprise architecture and AI practice. Its methods draw on more than two decades of architecture and transformation work in regulated financial environments across Canada and France.
Latest insights
8 min read
Prompt fluency is not enterprise AI maturity. The durable capabilities sit in strategy, integration, critical judgment and systemic design.
7 min read
Once AI changes data, decisions, roles and customer expectations, stopping a model is not the same as reversing the system.
9 min read
Retrieval does not create meaning. Enterprise AI needs authoritative sources, semantic context, provenance and feedback designed as an operating system.
Describe the decision, platform or operating risk that is slowing you down. We will identify the evidence required and whether consulting, training or a scoped agent is the right response.
