Reparo

Pattern Mix

Build covered the full engagement: workflow framing, business case, and shipping the production experience inside SMS and MMS so technicians could use it without changing workflows. The client retained operational ownership at launch. This engagement ran before Uplift offered the Operate retainer.

Business Context

Turn expert troubleshooting knowledge into a workflow field technicians could use in the moment, through channels they already had open, without forcing app adoption.

Business Relevance

Every extra minute diagnosing a job delayed service completion and made expert knowledge harder to access at the point of work.

Problem

Creating an accessible AI diagnostic tool that plumbers could use through SMS and MMS to get troubleshooting guidance in the field.

Solution

• Built an AI diagnostic agent with a natural-language SMS and MMS interface
• Integrated vision models for image analysis during troubleshooting
• Developed a multi-tenant SaaS architecture with Stripe billing
• Implemented idempotency patterns for reliable message handling

Approach

1. 1.Kept the experience inside SMS and MMS so the workflow matched how technicians already worked.
2. 2.Designed the architecture for reliability first because message duplication and bad field conditions were operating realities, not edge cases.
3. 3.Combined vision and language to reduce diagnosis friction, not to showcase model complexity.

Operating Impact

Diagnostic support moved closer to the job site. Less delay, expert guidance accessible without a new interface or workflow burden.

Business and Operating Outcomes

• +Lower adoption friction because the tool lived inside what technicians already used
• +Troubleshooting support available at the point of service, not back at the office
• +A delivery pattern that scales to broader field-service workflow automation

Technologies