Home services marketing intelligence platform came to Armakuni for aI call and form intelligence: model benchmarking and fine-tuning, data pipeline modernization, GenAI use case assessment, and multi-POC agentic AI commercial intelligence layer.
The challenge
Armakuni won the initial engagement when the company was still Blue Corona, before its merger with Ryno Strategic Solutions. The engagement began with a focused AI call analysis PoC that produced production-quality results fast enough to convince the C-Suite. After a six-month hold, Armakuni maintained communication and re-engaged, growing the account across data platform modernization, model benchmarking, voice intelligence assessment, and four parallel AI POCs covering the full commercial intelligence stack.
Scale: 150+ employees performing manual call analysis daily prior to AI engagement; platform processes tens of thousands of inbound calls across home services clients including HVAC, plumbing, and electrical contractors.
What we built
Armakuni delivered aI call and form intelligence: model benchmarking and fine-tuning, data pipeline modernization, GenAI use case assessment, and multi-POC agentic AI commercial intelligence layer. The engagement ran as multiple fixed-scope SOWs: Data Audit and Modernization PoC (Jan 2024, Nov 2024), Nova Model Benchmarking and Fine-Tuning (Oct 2025), New GenAI Use Case Discovery Assessment (Jun 2025), Prompt Framework POC, Enhancement Detection Engine POC, Forecasting and Budget Optimization POC, Anomaly Detection and Proactive Alerts POC (all Nov 2025). AWS funded the work at $25,000.
The outcomes
5 measurable outcomes shipped across the engagement. The ones that moved the business the most:
Ryno was production-ready in under two weeks of a four-week PoC. After an internal attempt that never reached production quality, Armakuni's AI call analysis feasibility PoC convinced Ryno to commit to production within the first half of the engagement.
A 150-person manual call analysis workflow is targeted for AI replacement. The PoC showed AI could perform the classification, disposition labeling, and outcome extraction 150 employees were doing by hand each day, and the platform is the foundation for eliminating that overhead in production.
Nova fine-tuning creates a path to materially lower AI operating cost. Armakuni's TCO analysis gives Ryno a structured Go/No-Go framework for moving to a fine-tuned Amazon Nova variant, a significant cut in per-call inference cost at equivalent accuracy.
A commercial intelligence layer was created where none existed. Enhancement detection, forecasting and budget optimization, and anomaly detection now identify missed revenue per call, validate marketing ROI, and catch performance issues before clients feel them.
The account was maintained through a six-month engagement hold. Armakuni kept consistent communication during the pause and resumed when Ryno was ready, demonstrating the partnership depth that drives sustained multi-year account growth.
Built on AWS
Delivered under our AWS AI Services, Data Analytics competencies.
What's next
Production deployment of Phase 4 POC capabilities across the platform; potential voice intelligence implementation following the GenAI assessment roadmap; ongoing model fine-tuning and optimization as Nova performance data matures.
