Results from AI-powered quality & delivery
Selected engagements where Agentic Software Quality and AI-native engineering cut release friction and defect escape.
Outcomes, not slideware
Representative engagements that show how AI-native engineering and autonomous QA move real delivery metrics.
Agentic Quality for a payments platform
Problem. Brittle Selenium suites delayed every release and burned 2 engineers on maintenance.
Solution. Deployed self-healing E2E agents across UI + API contracts with continuous canary gates.
Release cycle cut from 6 weeks to 11 days · 0% script babysitting
RAG copilot for customer support
Problem. Support volume grew 3× while answer quality varied across agents and shifts.
Solution. Built a grounded RAG assistant over docs + tickets, with escalation to humans.
42% fewer first-response escalations · 18s median answer latency
AI-assisted .NET modernization
Problem. A 12-year monolith blocked new features; documentation and tests were missing.
Solution. AI-generated architecture maps, migration plan, and regression suite before rewrite.
Migration roadmap in 3 weeks · test coverage from ~8% to 71%
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What engineering leaders say
Feedback from teams that moved from AI experiments to production systems with measurable delivery gains.
“cvalleysolutions didn't just add AI features — they rebuilt how we ship. Our QA agents heal themselves and releases finally stopped slipping.”
Director of Engineering
US Payments SaaS
“The readiness audit alone paid for itself. We knew exactly which use cases had ROI before writing a single prompt in production.”
CTO
LATAM FinTech
“Legacy modernization with AI documentation and generated tests was the unlock we needed. Clear plan, measurable progress, zero big-bang risk.”
VP Product
Enterprise Retail Platform