Case Study: Trilogy achieves enterprise-scale open-weight AI workflows with Fireworks AI

Trilogy cuts inference costs by 5x with Fireworks AI

Trilogy's AI Center of Excellence, overseeing hundreds of portfolio companies, faced escalating AI infrastructure costs and operational constraints like rate limits as AI adoption scaled across its enterprise. To address the prohibitive cost of proprietary models and these structural barriers, Trilogy sought to validate open-weight models and selected Fireworks as a primary inference infrastructure layer for evaluation.

Fireworks provided a production-grade inference solution that enabled Trilogy to standardize open-weight model usage and run billion-token scale agentic workflows. The implementation resulted in inference at approximately one-fifth the cost of proprietary systems, a 93.6% prompt cache hit rate, and the ability to sustain high-volume workloads, shifting the organization from constrained experimentation to scalable production.

Trilogy