How Faire used Decagon AI to scale customer support and cut operational drag

Faire, a wholesale marketplace connecting brands and retailers, worked with Decagon to automate repetitive support contacts and give its team better AI knowledge tools. The vendor story describes qualitative gains in efficiency, cost and team focus.

The problem

Faire needed to keep delivering strong customer experience while scaling efficiently. Processes such as initiating returns took considerable time and effort, and the team also had to manage operational costs while holding service standards.

How they did it

1. Deploy Decagon's Chat product as the AI support layer.
2. Automate and reduce repetitive customer contacts such as common inquiries.
3. Equip support teams with improved AI knowledge bases and processes.
4. Redirect human agents to complex cases, strategic work and customer experience insights.
5. Work with Decagon on feedback and ongoing improvements.

Results

• As reported by Decagon, support became more efficient and operational costs fell, with savings reinvested in customer experience.
• As reported by Decagon, processes such as returns were handled more smoothly, improving customer satisfaction.
• As reported by Decagon, the team gained speed by no longer depending as much on engineering and product resources.
• As reported by Decagon, support agents shifted toward strategic work and AI-driven customer enablement. No numeric metrics were published.

As reported by the source (Decagon customer story); AgentGid did not measure these figures.