Meet Gabbi, AI Conversational Platform
An AI-powered voice and chat intake platform with fine-tuned language models, a containerized microservices backend, and automated CI/CD.
Challenge
Meet Gabbi needed a backend that could keep up with an evolving AI assistant. Conversational products live on frequent model and prompt updates, and every one of those changes is a deployment risk if the infrastructure underneath isn't built for fast, safe releases.
Solution
We designed and implemented a microservices backend on Python/Flask, Docker, and AWS ECS, splitting retrieval, inference, and chat handling into services that could scale and deploy independently instead of shipping as one monolith. On the AI side, we layered in fine-tuned language models for natural dialogue and context-aware responses. We set up a GitHub Actions CI/CD pipeline that automated build, test, and deployment, and worked with product and frontend teams in an Agile setup to turn feature requirements directly into deployable pipelines.
Results
The automated pipeline cut release time by 30%, turning what used to be a manual, risky release process into a repeatable one, with infrastructure changes staying in step with product changes instead of trailing behind them.