RL finetuning method that ensures that the inference-time compute for queries is optimized based on query difficulty, leading to significant inference efficiency.

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

A Model Context Protocol (MCP) server that provides comprehensive customer sales database access for Zava Retail DIY Business. This server enables AI assistants to query and analyze retail sales data through a secure, schema-aware interface.