We’re launching Lyria 3.5 in Google Flow Music, with advances across musicality, lyrics, vocals, and creative control
deepmind.google·6d ago
AI Engineering
OpenAI Blog·Dec 11·5 min read
How Podium is arming 10,000+ SMBs with AI agents
TL;DR
Small and medium-sized businesses (SMBs) struggled to handle customer service at scale without expensive staff. Podium built Jerry, an AI agent powered by GPT-5 (OpenAI's language model), to automate customer interactions for Main Street businesses.
✦ Why It Matters
Engineers can apply large language models to automate customer-facing workflows, reducing operational costs while scaling service capacity.
Key Takeaways
- Deploy large language models like GPT-5 to automate repetitive customer interactions and reduce support overhead.
- Design AI agents to integrate seamlessly into existing business systems rather than requiring complete workflow redesign.
- Measure success through engagement metrics and customer satisfaction, not just cost reduction.
- Target SMBs as early adopters; they benefit most from automation due to resource constraints.
Full Summary
Main Street SMBs faced a critical gap: scaling customer service operations required hiring more staff, which was costly and difficult. Podium leveraged GPT-5, OpenAI's advanced large language model (a neural network trained on vast text data to generate human-like responses), to create Jerry—an AI teammate that handles customer conversations autonomously.
Jerry integrates into existing business workflows and responds to customer inquiries in real time. The deployment reached over 10,000 SMBs across various industries.
Measured outcomes showed 300% growth in customer engagement metrics, indicating substantially higher interaction volume and customer satisfaction. This demonstrates that AI agents can effectively augment human teams in service-oriented businesses without requiring extensive retraining or infrastructure overhaul.