The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
AI Voice Agents for Businesses π€π
Your customers shouldn't have to wait for someone to answer.
I build AI Voice Agents that can answer customer calls, have natural conversations, collect information, qualify leads, answer frequently asked questions, and connect with your existing business workflows.
Perfect for businesses that receive customer calls and want to:
β Reduce missed calls
β Respond faster
β Capture more leads
β Automate repetitive conversations
β Save staff time
β Improve customer experience
If your business receives calls from customers, there is a good chance part of that process can be automated.
Interested in seeing how an AI Voice Agent could work for your business?
Send me a message.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Trending
retrofuturism
Share your favorite designs from the past exploring the distant future. Or your own take on the aesthetic π
halftone
Dots. Texture. Grain. Let's see your designs using the halftone technique.
Midjourney
Creatives are showing off what they're making with Midjourney.
colorgrade
Video editors sound off: How do you enhance the mood of your video in color grading?
Related posts
π¨ MOST PRODUCTIVITY APPS DONβT HAVE A RETENTION PROBLEM.
THEY HAVE A VALUE-COMPOUNDING PROBLEM.
They help users capture more:
π More notes
π More links
πΈ More screenshots
ποΈ More voice memos
But a larger archive does not automatically become a more valuable product
The real test starts later:
β WHAT HAPPENS AFTER THE USER HAS ALREADY CAPTURED 300 THOUGHTS?
That is where most products quietly fail. Because the archive grows. But the userβs understanding does not.
A voice note from Monday.
A screenshot from Thursday.
An article saved two weeks later.
A sentence typed at 1 AM.
Individually, they look unrelated.
But sometimes they are the same unresolved question appearing in different forms.
And this is where AI becomes genuinely interesting.
Not when it summarizes another note.
Not when it rewrites another paragraph.
Not when it gives users another chat box.
But when it recognizes:
π§ YOU HAVE BEEN CIRCLING THE SAME PROBLEM FOR 12 DAYS.
For this concept, the core mechanic was built around one distinction:
β‘ FREQUENCY IS NOT REPETITION.
REPETITION IS EVIDENCE.
A thought mentioned once may be noise.
A thought mentioned four times across different contexts may be a signal.
And a product that can detect that signal can create value a normal archive cannot.
01 - CAPTURE
ποΈ The thought should enter the system before it disappears.
No folders.
No tagging.
No forced structure.
02 - UNDERSTAND
AI extracts the underlying meaning.
βMaybe onboarding should get people to value fasterβ¦β
becomes:
π‘ REDUCE TIME TO FIRST VALUE.
That is already more useful than transcription. But it is still not the interesting part.
03 - CONNECT
The system sees another thought about activation.
Then an article about onboarding. Then a screenshot. Then another voice note. Now the product has enough context to say:
π YOU KEEP COMING BACK TO THIS.
4 mentions.
12 days.
At that moment, the system is no longer helping the user remember information.
It is helping the user recognize importance.
04 - TURN CONTEXT INTO VALUE
This is where the growth logic changes. Most retention loops ask users to come back and repeat the same action:
π Create another note
π Track another habit
π½οΈ Log another meal
β
Complete another task
A stronger loop can work differently:
π EVERY NEW INPUT INCREASES THE VALUE OF PREVIOUS INPUTS.
The product becomes better not simply because the user used it more often, but because accumulated context creates new insight. That creates compounding value.
Day 1:
The product understands what you said.
Day 10:
It understands what keeps repeating.
Day 30:
It may understand what deserves action.
That is a much more defensible form of retention. Because the userβs history is no longer just stored data. It becomes product intelligence.
β¨ AI SHOULD NOT JUST HELP USERS PRODUCE MORE.
IT SHOULD HELP THEM NOTICE WHAT THEY ARE ALREADY REVEALING THROUGH THEIR OWN BEHAVIOR. That is where a note-taking product stops being an archive. And starts becoming a thinking system.
π FULL CASE STUDY BELOW
π BOOK A MOBILE APP SESSION
I'm so excited!!! I made this cinematic scene using seedance 2.5. All I can say is wow... this is amazing.
Really impressive work
Excited to share my submission for the #contraseedancechallenge π¬
I created this AI movie trailer using CapCut Video Studio and Seedance 2.5, focusing on cinematic visuals, dramatic moments, and a strong movie trailer feel.
I wanted to explore how AI can bring a film idea to life and create a story that makes people want to see what happens next.
Created with: CapCut Video Studio + Seedance 2.5
What do you think of the trailer? ππ₯
Amazing work
