Ajay Kumar

A user on r/ElevenLabs described their cloned voice as "too pristine - like the AI restored my voice to a younger, less character-filled version of itself."

That one sentence nailed it. Most cloning models are trained on clean, professional audio.
So when your voice goes in, it doesn't just get copied, it gets corrected.
The rasp smoothed out, the pacing evened, and the natural drop in energy at the end of a thought, gone.
Technically better audio. Emotionally hollow output.
A November 2025 study from Queen Mary University found listeners are fooled by synthetic voices more than half the time.
But fooled isn't the same as convinced. Something feels off. They just can't name it.
What they're feeling is the absence of imperfection. The fingerprints that make a voice actually yours.
Most tools optimise for clean. However, we are taking a little different road than just clean.
We built Velo's voice clone to optimise for you - preserving the rhythm, texture, and natural unevenness that makes your voice recognisable as yourself.
Our new feature launch is also around perfecting voice clones and streaming them faster.
This is such an exciting time to be in this AI space. Would love to connect with any fellow builder in AI voice cloning space.
Let's catch-up and exchange ideas, what say?

Things have been moving really fast at Velo. 

The pace at which we're building based on feedback has honestly been a bit crazy, in a good way.

We're shipping, iterating, and learning fast.

After 18+ years in the IT industry, I'm fascinated by how we build things today. I rely heavily on AI-assisted "vibe coding" for rapid prototyping, but when it comes to the core logic, I'm all about the strictness and performance of Rust.

Here is what I'm currently juggling:

Writing about programming and technology in my blogs on Hackernoon and Dev.to;