CallDelivery: AI Coach for Sales Rep Delivery Skills

After 1 week of coding, I just deployed my SaaS (Vercel/Fly.io) — Looking for 20 brave beta testers!

Shipping a functional SaaS in a week from agency background is a solid achievement, well done on getting it out the door. The zero-user stage is the hardest part. A few thoughts on the positioning and the technical side: \*\*The problem space:\*\* You're tackling an interesting angle. Most sales intelligence tools (Gong, Chorus) focus entirely on the "what" — talk track adherence, competitor mentions, objection handling. Focusing purely on the "how" (delivery, pacing, filler words) is a good wedge, especially for junior reps or founders doing founder-led sales who haven't built that muscle yet. \*\*The upload friction:\*\* Since you mentioned testing the backend upload — getting sales reps to manually upload video files of their calls is usually the biggest point of failure for tools like this. It's too much friction for a daily workflow. If the analysis is good, your immediate next priority should be figuring out how to pull the recordings automatically via API (Zoom, Google Meet, or whatever dialer they use). If it doesn't happen automatically in the background, usage will churn after week two. \*\*Feedback on the Vercel/Fly.io stack:\*\* That's a very solid, modern stack. [Fly.io](http://Fly.io) is great for the heavy lifting (like video processing/AI inference) while keeping Vercel for the frontend delivery. Watch out for cold starts on Fly if your instances spin down to zero, especially for file uploads — you might get timeouts if a large video hits a cold machine. I'll grab one of the codes and run a recent demo call through it to see how the analysis holds up. Good luck with the launch!

Shipping a functional SaaS in a week from agency background is a solid achievement, well done on getting it out the door. The zero-user stage is the hardest part. A few thoughts on the positioning and the technical side: \*\*The problem space:\*\* You're tackling an interesting angle. Most sales intelligence tools (Gong, Chorus) focus entirely on the "what" — talk track adherence, competitor mentions, objection handling. Focusing purely on the "how" (delivery, pacing, filler words) is a good wedge, especially for junior reps or founders doing founder-led sales who haven't built that muscle yet. \*\*The upload friction:\*\* Since you mentioned testing the backend upload — getting sales reps to manually upload video files of their calls is usually the biggest point of failure for tools like this. It's too much friction for a daily workflow. If the analysis is good, your immediate next priority should be figuring out how to pull the recordings automatically via API (Zoom, Google Meet, or whatever dialer they use). If it doesn't happen automatically in the background, usage will churn after week two. \*\*Feedback on the Vercel/Fly.io stack:\*\* That's a very solid, modern stack. [Fly.io](http://Fly.io) is great for the heavy lifting (like video processing/AI inference) while keeping Vercel for the frontend delivery. Watch out for cold starts on Fly if your instances spin down to zero, especially for file uploads — you might get timeouts if a large video hits a cold machine. I'll grab one of the codes and run a recent demo call through it to see how the analysis holds up. Good luck with the launch!