In March 2025, Chibexme developed a unified service adapter for the Shubhamsaboo/parlant repository, enabling provider-agnostic access to large language models. By integrating LiteLLM and architecting a flexible backend interface, Chibexme allowed seamless switching between multiple LLM providers, reducing vendor lock-in and supporting rapid experimentation. The solution was implemented using Python and leveraged skills in API integration, backend, and full stack development. This work established a scalable foundation for future AI integrations, simplifying the addition of new providers and improving adaptability for evolving business needs. No major bugs were addressed during this period, reflecting a focus on foundational feature development.