Zendesk integrated OpenAI's models to create adaptive AI service agents that autonomously manage customer conversations and execute resolution tasks. They implemented a multi-agent architecture featuring task identification, conversational RAG, procedure compilation, and procedure execution agents integrated with existing support workflows through API calls and natural language procedure definitions, while providing real-time chain-of-thought visibility. This solution transitions from traditional intent-based bots to a hybrid model of scripted and generative reasoning, streamlining customer service processes.

Hebbia built Matrix, a multi-agent AI platform that orchestrates OpenAI models including o3‑mini, o1, and GPT‑4o to automate complex financial and legal research tasks. The platform decomposes intricate queries into structured analytical steps and integrates modules like OCR, hallucination validation, and artifact generation to process complete documents, creating an infinite effective context window. This solution streamlines due diligence, contract review, and market research workflows, drastically reducing manual processing time.

Factory built a command center for software development by embedding OpenAI’s reasoning models directly into its platform’s workflows. They integrated specific models—using o1 for complex architectural planning, o3‑mini for rapid exploration and bug triage, and GPT‑4o for real-time code generation—across various stages of the development lifecycle. This implementation streamlined coding, design, review, and knowledge retrieval processes by reducing manual research and minimizing context switching, enabling developers to focus on high-leverage tasks.

Endex built an AI Analyst platform that leverages OpenAI's reasoning models (GPT‑4o, o1‑mini, o1‑preview, o3‑mini, and o1 vision) to retrieve, analyze, and synthesize complex financial data. The solution integrates internal data, public disclosures, and financial reports to automate processes such as due diligence, earnings analysis, and investment committee memo preparation using reinforcement learning fine-tuning and performance tracking, transforming traditional manual workflows into streamlined AI-driven processes.