Workflow operations
50+ automation and data workflows delivered across client environments
Through Data Management, Juan has led AI, automation, and reporting work spanning discovery, solution design, implementation planning, and delivery oversight.
Typical problems
- Manual reporting and admin-heavy processes
- Slow follow-up and fragmented internal workflows
- AI experiments that were not production-ready
Delivery pattern
- Identify the highest-friction workflow first
- Build the smallest useful operator or automation
- Add guardrails, approvals, and measurable outcomes
Enterprise data + AI
Modernized analytics and ML delivery for operations-heavy environments
At Canoo and in prior enterprise roles, Juan helped build and scale cloud data pipelines, dashboards, and ML-enabled workflows used for operational insight and decision support.
What changed
- Faster access to operational data
- Better visibility for stakeholders using dashboards and reporting
- Stronger foundations for predictive and AI-assisted use cases
Why it matters
- Proves delivery beyond demos and prototypes
- Connects AI work to data quality and business operations
- Supports implementation work in more complex client stacks
AI + automation outcomes
Reduced operational friction with AI-enabled workflows
Earlier delivery work included analytics, IoT, and AI-assisted process improvements that reduced turnaround time, improved visibility, and lowered support/admin load.
Representative themes
- Workflow automation for support and operations teams
- Analytics systems that improved response and reporting speed
- Security-aware implementation with real delivery constraints
What clients buy now
- A fast first win instead of a long strategy deck
- Operator-style systems that work across real tools
- Clear next steps after the first deployment proves value
