Canonical AI
Analytics for Your Voice AI Agent
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Tom Shapland

Canonical AI - Analytics for your voice AI agent

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Canonical AI
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We help Voice AI developers improve their agents. We map caller journeys. We show you where and why callers are dropping off. We provide audio metrics (i.e., latency) and conversational metrics (i.e., query for cases where callers ask for a representative).

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Rachel Bradley
Awesome idea, would appreciate a better understanding of how you built it
Adrian Cowham
Maker
@rachel_bradley2 Happy to share, let's connect and have a chat.
Tom Shapland
Maker
@rachel_bradley2 Adrian is the right guy for that. I'm just the guy that does the launches :).
Huzaifa Shoukat
Huge congrats to the Canonical AI team on today's launch! I love how you're shedding light on the blind spots of voice AI interactions. Here's a curious question: Can your platform also provide insights on how to improve the success rate of resolving caller queries without escalating to a human rep, or is that a future roadmap item?"
Adrian Cowham
Maker
@ihuzaifashoukat Yes! For example, we can user points of frustration, like having to repeat a phone number. Would love to chat in depth about this with you!
Chuck Fields
This is a super cool product. We need to have more insight into what AI is doing behind the scenes. Having this sort of high level analytics is crucial for any business with voice AI agents.
Tom Shapland
Maker
@chuck_fields Thank you for your support and encouragement!
Lucas Campa
A great idea well executed - highly usefulf or voice AI teams like us!
Tom Shapland
Maker
@lucaswcampa thank you, Lucas! Love what you're building at Toby!
Luke Harries
Congrats on the launch! What’s been the most surprising learning your customer has had with your analytics?
Tom Shapland
Maker
Thank you, Luke! We're excited to work with developers using 11labs new Voice AI agents. Some of the interesting problems include... - The AI just stops responding. In one case, the root cause is with a third-party provider's API. The developer built in a backup provider to handle the error case. - The caller hangs up before giving the AI a chance to solve the issue. When developers delay in the conversation design the fact that it's an AI, success rates go up. - The AI calling from the wrong list. The caller's kept saying on one of the sad paths, "I've never heard of your company." Lead qualification is a fast growing use case of Voice AI. But you can only call back leads who have consented (i.e., through an online form) to be called. In this case, the Voice AI developer went to their customer and gave them the insight that they were not curating their lists correctly. A win for the voice ai dev!
nina k
Great team. Tom is a leader in Voice AI.
Tom Shapland
Maker
@ninacali4 You flatter! That means a lot to me coming from you! Daily paved the way for the rest of us in Voice AI.
Richard Song
Congratulations on the launch, Tom! Go YC alum!
Tom Shapland
Maker
@renchu_song thank you!
Alan Wells
This is awesome! The drivers of AI agent performance are often so opaque when running in production at scale. I think Canonical will be one of those things where, looking back, it will be hard to imagine that we deployed voice agents without the types of insights that Canonical provides.
Tom Shapland
Maker
@alanwells thank you! We share that same vision!
Vincent Wilmet
voice devs unite!
Tom Shapland
Maker
@vincentwilmet haha, yes!
Jonny Miles
Imagine Tesla will want to use this on their robots soon 🤖. Congrats on the launch!
Tom Shapland
Maker
@jonnymiles thank you!
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