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Digid AI automation

Automate the workflow that is already costing time.

Digid helps Canadian SMEs choose, design, and govern practical AI automation. The work starts with one business process, clear data, human approvals, and a measurement point before connecting more tools.

Good first candidates

Start where the team repeats the same work, uses the same documents, or loses time moving information between systems.

Good first version

The first version should be narrow enough to test with real users and useful enough to show a measurable before-and-after signal.

Good first controls

Permissions, review points, logs, escalation paths, and owner responsibilities are defined before automation starts acting for the business.

Automation examples

Sales and service intakeCapture requests, classify priority, draft replies, create CRM tasks, and route exceptions to the right person.
Document reviewSummarize source documents, compare requirements, draft responses, and keep approved references visible.
Reporting handoffsPull signals from CRM, forms, spreadsheets, documents, or operational systems into a repeatable report.
Quality and operationsTurn checklists, photos, notes, tickets, and production evidence into searchable action records.

What Digid clarifies before build

Workflow owner
Who owns the process, exceptions, approvals, and maintenance?
Data sources
Which systems, files, and records can AI use safely?
Review points
Which outputs need a person before action?
Measurement
What time, quality, response, or cost signal proves value?

Where automation usually connects

Most projects touch more than one system. Digid maps the handoff between CRM, calendar, chat, email, documents, spreadsheets, cloud storage, reporting dashboards, and AI assistants. The first version should use the smallest reliable stack that can be tested by the people doing the work.

If your team already uses CRM and marketing automation, Google Workspace, Microsoft 365, Slack, Cloudflare, Azure, AWS, or Google Cloud, Digid can start from the tools already in place before recommending anything new.

When to clean up first

Automation should wait when the process is unclear, source data is unreliable, approvals are undefined, or the team cannot describe a good output. In those cases, Digid starts with workflow cleanup, AI onboarding, or a readiness review before build work.

What you leave with

  • A short workflow map showing users, systems, data, decision points, and risks.
  • A practical automation scope for the first useful version.
  • A governance checklist for permissions, review, logging, and escalation.
  • A next-step route: self-funded sprint, funding-supported plan, AI onboarding, or no-build process cleanup.

Related Digid paths

Use the broader adoption path if you are still deciding the workflow. Use AI onboarding if the team needs rules, training, and usage habits before automation. Use funding readiness when the workflow may become a grant, loan, or SR&ED-supported project.

Start with one workflow.

Use AI Pathfinder if you are comparing possible workflows. Book a review if you already know the process you want to automate and need help deciding what to build, govern, and measure.

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