“We don't know where AI would help.”
AI opportunity review
A practical recommendation for where AI could help your team first.
- Prioritized AI use cases
- Tool options and data constraints
- A recommended first step
Put AI to work in your organization.
Find the right use cases, test what works, and put useful AI into a workflow your team can own.
Book a discovery call
See a sample deliverable 20-minute introductory call.
Fixed scope and price
Agreed before the engagement starts.
Documented handover
Code, setup notes, training materials, or written recommendations, depending on the service.
Data access and handling
We agree which data and tools to use, who can access them, and where human review is needed.
Ways to put AI to work.
Start with a written review of where AI could help, or connect an approved tool to one defined workflow. Scope, deliverables, and price are agreed before work starts.
“We know the task we want to improve.”
AI integration
Connect an approved AI tool to one defined workflow and test the result with your team.
- One agreed workflow and named systems
- Tests and human review points
- Setup notes and a named owner
Explore all services
Have a defined idea to test? Explore the AI proof of concept.
Templates and checklists to use on your own. Browse the starter packs.
See what useful looks like.
An illustrative internal guidance assistant: a question, a clear answer, and a link to the source.
See a sample deliverableWhat stands between interest and adoption?
Security and privacy concerns can delay AI adoption. Start with the practical questions: what can a tool reach, what information goes into it, and who decides how it is used?
% of businesses, by size, Q2 2026
Cybersecurity or privacy concerns as a barrier that limits AI use
View as tableView as chart
| Category / period | Share (%) |
|---|---|
| All businesses | 13.4% |
| 1 to 4 employees | 11.6% |
| 20 to 99 employees | 22.3% |
| 100 or more employees | 30.0% |
Source: Statistics Canada, Canadian Survey on Business Conditions, Q2 2026 (June 11, 2026) · Retrieved
From a question to a useful system.
A proof of concept becomes easier to understand when you can see how the parts connect.
Illustrative process. Scope, data access, and acceptance criteria are agreed for each engagement.
The complete workflow is shown below.
Using your device’s reduced-motion setting. The complete workflow remains visible.
Motion paused. The complete workflow remains visible.
Compact view: a complete workflow is shown above the stages.
Short window: a complete workflow is shown beside the stages.
Scroll through the four stages. The diagram follows the explanation.
1 / 4
Understand the work.
Start with the task, the people doing it, and the information they use. Agree what a useful result would look like.
A clear question. An agreed boundary.
2 / 4
Make the connections.
Build a focused prototype around the agreed task. Connect only the documents and tools needed for the example.
A working example to examine.
3 / 4
Check what comes back.
Evaluate the output against the agreed cases. Look for missing answers, conflicting sources, and places where human review is needed.
Evidence, limitations, and a decision.
4 / 4
Leave a clear next step.
Bring together the code, setup notes, evaluation evidence, and operating assumptions. Recommend whether to proceed, revise, or stop.
A documented handover. Production work is scoped separately.
Illustrative workflowAll four stages
AI adoption in Canadian businesses.
Figures from Statistics Canada's Canadian Survey on Business Conditions and the Bank of Canada's Business Leaders' Pulse.
View more Canadian AI research
% of businesses, Canada
Businesses using AI to produce goods or deliver services
View as tableView as chart
| Category / period | Share (%) |
|---|---|
| Q2 2024 | 6.1% |
| Q2 2025 | 12.2% |
| Q2 2026 | 19.2% |
Each survey asks about use in the preceding 12 months. Periods depend on when a business responded.
Source: Statistics Canada, Canadian Survey on Business Conditions, Q2 2026 (June 11, 2026) · Retrieved
% of firms, December 2025
Use of AI in core business operations
View as tableView as chart
| Category / period | Share (%) |
|---|---|
| Significant use | 8% |
| Moderate use | 21% |
| Low use | 29% |
| Plan to start in the next 12 months | 11% |
| Not using, no plans | 28% |
| Don't know | 3% |
Business Leaders' Pulse respondents are a different survey population from the Statistics Canada figures.
Source: Bank of Canada, Business Leaders' Pulse, December 2025 (Sparks at Bank, August 2026) · Retrieved
% of AI-using businesses, Q2 2026
Most common AI applications among businesses using AI
View as tableView as chart
| Category / period | Share (%) |
|---|---|
| Data analytics | 36.6% |
| Text analytics | 34.5% |
| Virtual agents or chat bots | 28.2% |
| Natural language processing | 27.0% |
| Large language models | 24.8% |
| Speech or voice recognition | 20.6% |
Source: Statistics Canada, Canadian Survey on Business Conditions, Q2 2026 (June 11, 2026) · Retrieved
Before we begin.
Do we need to know which AI tool to use?
No. An AI opportunity review can help identify useful tasks and compare tools against your budget and data constraints. The recommendation may be to use an existing tool, improve a process, or leave a task as it is.
Can you help with tools we already use?
Yes. We can assess how an existing AI tool fits your work, connect one agreed workflow where the tools support it, or train your team to use it. We confirm access, licensing, data handling, and scope before starting.
Is training suitable for a non-technical team?
Yes. We agree the roles and experience level in advance and use practical examples from the team's work. Sessions include checking outputs and understanding what business information can be shared.
What will we receive from a proof of concept?
A working prototype, code, documentation, an evaluation against the agreed criteria, and a recommendation on next steps. The exact deliverables are agreed in the scope.
Is a proof of concept ready for production?
A proof of concept tests an idea on your data. Production deployment is separate work with its own scope.
How is the price decided?
We agree a fixed scope and price before the engagement starts. The discovery call helps establish what the work needs to cover.
What should we prepare for the discovery call?
Bring a short description of the problem, the tools you use, and any timing constraints. No slide deck is needed. Do not email confidential documents or credentials to arrange the call.
What do you need access to, and what do you not want?
We agree the smallest useful set of screenshots, exported settings, or policy documents for the scope. Do not send passwords, API keys, administrator credentials, production secrets, or customer records to arrange a call. Any system access needs a separate agreement. Read about data handling.
Who does the work?
Jay Rodrigues works directly with your team from scoping through delivery.
Can you work with our existing security team or MSP?
Yes. We agree responsibilities, access, and handover with your team or managed service provider. Configuration changes, remediation, and ongoing operation stay with the agreed owner unless separately scoped.
Do you work outside Ontario?
The practice is based in Ontario and serves Canadian organizations. We confirm delivery arrangements and any location or sector requirements during scoping rather than assume the same rules apply everywhere.
Understand. Make. Put to work.
Start with a discovery call.
Describe the task or problem you want help with. We will discuss whether we can help and what the work would involve.
Book a discovery call
20-minute introductory call.