AI Stack Planning
A full AI tool stack blueprint across departments: foundation models, tools, orchestration, governance, and cost guardrails. With a 12-18 month sequence.
What is AI stack planning?
AI stack planning is a consulting engagement that designs the full set of AI tools, models, orchestration, and governance an organization needs, and the order in which to deploy them, over a 12-18 month horizon. ChatGPT.ca delivers AI stack plans for Canadian businesses that cover six layers (foundation models, AI tools and SaaS, orchestration and agents, governance, cost guardrails, sequencing) with explicit build-vs-buy recommendations for every capability.
The six stack layers
Every layer addressed. No “AI strategy” hand-waving.
Foundation models
Which LLMs and where: OpenAI, Anthropic, Google, Llama. Build-on, embed, or self-host.
AI tools & SaaS
Off-the-shelf tools by category: copy, coding, research, sales, support, ops. With pricing.
Orchestration & agents
How tools connect: Make, n8n, custom orchestration, agent frameworks, MCP servers.
Governance layer
AUP, vendor data-handling matrix, PIPEDA gap check, incident response runbook.
Cost guardrails
Per-team budgets, usage triggers, FinOps practices for AI, model selection by cost.
Sequencing
12-18 month rollout sequence by capability, with dependencies and decision gates.
How the engagement runs
Discovery
Workflow audit, current AI tool inventory, stakeholder interviews across departments.
Stack Design
Six-layer stack drafted with vendor / build recommendations and cost estimates.
Sequencing & Guardrails
12-18 month rollout sequence, per-team budgets, governance layer, PIPEDA gap check.
Review & Handover
Executive readout, working session with IT / ops, written blueprint delivered.
Investment
Department
- ✓Single department
- ✓Foundation + tools layer
- ✓12-month sequence
Company-Wide
- ✓Multi-department
- ✓Full 6-layer stack
- ✓18-month sequence
- ✓Cost guardrails included
Enterprise
- ✓Multi-business-unit
- ✓Custom stack architecture
- ✓PIPEDA gap analysis
- ✓Quarterly review for 12 months
Frequently Asked Questions
How is this different from the ChatGPT Stack Plan?
ChatGPT Stack Plan is a 1-week, ChatGPT-specific blueprint (plan tier, add-ons, rollout). AI Stack Planning is broader: it covers your entire AI tool stack across departments, including LLM platforms, automation, agents, RAG, vector DBs, observability, and governance. Stack Plan is a focused starter; Stack Planning is the full enterprise picture.
How is this different from Vendor Selection?
Vendor Selection picks the right vendor for one job. Stack Planning decides what jobs there are, what should be one vendor vs many, and how the stack evolves over 12-18 months. Most enterprise clients run Stack Planning first, then Vendor Selection for each category.
Do you cover build vs buy decisions?
Yes, that is half the engagement. For each capability we recommend: buy an existing tool, build a thin wrapper on a foundation model, or build custom. The recommendation includes cost estimates, time-to-value, and ongoing maintenance burden so the decision is defensible.
What about cost guardrails?
Each tool in the recommended stack gets a budget envelope and a usage trigger that says "if monthly spend exceeds X, here is what to do." We also recommend FinOps practices for AI specifically: per-team budgets, token tracking, model selection guardrails.
How long does the engagement take?
Standard engagement is 4-6 weeks. Enterprise (multi-business-unit) can run 6-10 weeks. Includes 1 week of discovery, 2-3 weeks of analysis and stack design, and 1-2 weeks for review and handover.
What about governance and PIPEDA?
Every stack plan includes a governance layer: AI acceptable-use policy, vendor data-handling matrix, PIPEDA gap check, and an incident response runbook. For organizations needing full compliance documentation we pair this with PIPEDA-Ready AI Rollout.
Trying to plan AI across the whole company?
A 30-minute call will tell you whether stack planning is the right starting point.
Book a Discovery Call