SaaSCloud & DevOps
How We Helped a First-of-its-kind Communication and Voice AI Platform Achieve a 90% Positive Engagement Rate
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The Challenge
The client had built an innovative Voice AI platform but was spending nearly 40% of engineering bandwidth on deployment and maintenance operations.
Fragile CI/CD pipelines, inconsistent environments across cloud providers, and a lack of observability were slowing feature velocity and causing intermittent production incidents that hurt their NPS.
Our Approach
- Re-architected CI/CD pipeline using GitHub Actions with a blue/green deployment strategy
- Containerised all AI services with Docker and orchestrated via Kubernetes (EKS)
- Implemented infrastructure-as-code using Terraform across AWS and GCP
- Built a real-time model monitoring dashboard tracking latency, accuracy drift, and error rates
- Reduced mean time to recovery (MTTR) from 4 hours to under 20 minutes
Results
40% reduction in time spent on deployment and maintenance tasks
90% positive user engagement rate achieved post-infrastructure overhaul
3× faster feature release cycle — from biweekly to continuous delivery
Zero critical production incidents in the 6 months following re-architecture
Related Services
This project drew on our work in Cloud & DevOps, Product Engineering & Consulting.
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