Tribi.io — End-to-End
AI Development Pipeline

The Challenge

Tribi.io needed to ship AI-powered features faster without sacrificing quality. Their existing development workflow wasn’t designed for the rapid experimentation that AI products demand — every new feature required manual data pipeline setup, model evaluation, and integration testing that slowed iteration to a crawl.

The Solution

We designed and built an end-to-end AI development pipeline that streamlined Tribi.io’s entire product iteration cycle — from data ingestion and model orchestration to deployment and monitoring. The pipeline turned weeks of manual work into repeatable, automated workflows.

• Automated data ingestion and preprocessing pipelines for training and evaluation datasets
• LLM orchestration layer for chaining models, managing prompts, and A/B testing outputs
• CI/CD integration for seamless deployment of AI features alongside application code
• Evaluation framework with automated quality scoring and regression detection
• Monitoring dashboard for tracking model performance, latency, and cost in production

The Outcome

Tribi.io’s feature iteration cycle dropped from weeks to days. The team can now prototype, evaluate, and ship AI-powered features with confidence — spending less time on infrastructure and more time on product differentiation.