Businesses can access endless analytics but still struggle to decide what should be fixed first, why it matters and what good looks like.
← All work
Working product / capabilityDigital intelligence & opportunity platform
DigiM8
Turn scattered digital signals into prioritised action.
DigiM8 evaluates websites, search visibility and market evidence, then converts findings into a practical growth backlog.
PythonFastAPIPostgreSQLPlaywrightSearch dataLLMsDocker
A digital health and intelligence platform that consolidates evidence, scores meaningful areas and recommends concrete next actions.
03 / System shape
The useful part is how the components become one workflow.
04 / What this proves
A working example of joined-up engineering.
AI output becomes more useful when evidence and prioritisation are structured.
Research, analysis and publishing can become one repeatable system.
The platform can turn broad marketing data into accountable next actions.
05 / The engineering
How the system is put together.
- Automated website and search evidence collection
- Structured scoring and prioritisation
- AI-assisted interpretation and recommendation
- Account and business-level reporting
- Reusable proposal and playbook generation
06 / The trade-offs
Deliberate architecture choices.
- Prefer explainable evidence over opaque aggregate scores
- Use AI to prioritise and interpret rather than invent facts
- Keep recommended work tied to observable business context
07 / What became possible
The result is working capability.
These are capability outcomes rather than invented client metrics. Commercial measures can be added as the products are deployed and benchmarked.
01
A single view of digital health and opportunity
02
Recommendations linked to supporting evidence
03
Clearer sales and delivery conversations
04
A repeatable framework for ongoing improvement
More working evidence
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