How Phidiax’s Minimal Viable Experiment for AI unlocked real-time estimation in the restoration industry
Manual estimation was slowing down field operations. In weeks, Phidiax partnered with Restora, a veteran-owned restoration and reconstruction company, to prove that Agentic AI could cut cycle times by 80 percent. Applying our Minimal Viable Experiment for AI (MVE for AI) methodology, we delivered a working prototype that demonstrated measurable value and future potential. Restora’s openness to innovation and rapid experimentation played a pivotal role in the success of this initiative, which resulted in the creation of the Swiftimate estimation platform.
Client Name: Restora
Product Name: Swiftimate
Industry: Restoration
Location: United States
Summary: Restora is a veteran-owned restoration and reconstruction company recognized for military precision, rapid response, and a customer-first mindset. Through this engagement, Restora incubated Swiftimate, an intuitive, AI-enabled estimation platform that empowers contractors to generate professional estimates and invoices in minutes, with real-time voice input, backend integrations, and a streamlined quoting process.
Restora’s estimation process relied on verbal field recordings, manual transcription, and spreadsheet-based calculations. This created significant inefficiencies:
Delays in generating quotes
Inconsistent pricing and scope definitions
Limited visibility into performance trends
The hypothesis was that Agentic AI could automate transcription, apply semantic logic, and generate structured estimates in real time, without disrupting existing workflows. This experimental approach allowed Restora to validate the feasibility of AI-driven estimation before committing to full-scale development.
Approach Summary: Phidiax applied its MVE for AI framework to rapidly prototype an Agentic AI-powered estimation engine. The experiment used real-world data and live field recordings to validate the hypothesis and demonstrate impact in just weeks.
Implementation Highlights:
Timeline: 3-5 weeks
Technologies: Azure AI Foundry, SwiftimateAI, Azure Logic Apps, Azure Functions
Deliverables:
Real-time transcription and estimation from mobile recordings
Feedback loop architecture for accuracy improvement
Training for field teams and analysts on usage and interpretation
At a Glance:
80% reduction in estimation cycle time
Real-time access to estimates via mobile dashboards
Improved consistency and accuracy across job types
Detailed Outcomes: The MVE for AI eliminated manual bottlenecks and proved that Agentic AI could deliver structured, reliable estimates directly from field input. Analysts gained visibility into trends, while field teams received instant feedback. The feedback loop made the system smarter with every use.
“This experiment showed us how AI could fit into our workflows without disruption. The results were immediate and measurable.”
-Analyst, Swiftimate
The MVE for AI validated that Agentic AI could streamline estimation without disruption. With this confidence, Restora is now moving toward a Minimum Viable Product (MVP), a scalable, productized version of Swiftimate. This ensures experimental insights translate into sustainable business capabilities.
Restora is also partnering with Phidiax to expand into predictive modeling, scenario-based pricing, and anomaly detection. The Swiftimate prototype now serves as a blueprint for future AI-driven workflow modernization.
This engagement reflects Phidiax’s focus on AI Solutions and Digital Enablement, helping organizations validate innovation quickly and at low risk.
Ready to validate AI in your workflows? Explore our Minimal Viable Experiment for AI and see measurable results in weeks.
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