Handle sales and support calls with a voice agent
A team deployed an AI voice agent for after-hours calls, FAQs and order status, capturing structured call data for CRM and support systems.
Done with a custom-built or unnamed agent
- What they did
- The team put an AI voice agent into production for inbound sales and customer support, starting with lower-friction support calls such as after-hours coverage, FAQs, order status, and simple care requests. They tested multiple platforms and chose Feather because it handled inbound and outbound calls with the same conversational logic and wrote structured call data back into CRM and support systems; the post says the key was making it feel like a junior rep that could listen, clarify, and escalate rather than follow an IVR-style tree.
- How it went
- They report support calls were the easiest successful use case, while sales qualification worked but was much harder because slightly scripted conversations increased hang-ups. The post says Feather was not perfect, but held up under real call volume better than polished demos.
- Worth knowing
- The main catch was conversation quality: low latency and natural interruption handling mattered, and if the agent sounded scripted, results dropped fast.
Try it yourself with Lindy
Set up a voice agent for [my business] that answers after-hours calls, handles FAQs from [doc or website link], and gives order status from [system]. For each call, capture the caller's name, number, reason, and outcome, and log it to [CRM or helpdesk]. Escalate anything it can't answer by messaging me at [contact], and show me a test call before it goes live.
Source: Reddit · Undated
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