CyberCloud CallController: small, complete, and built on everything the cloud does well

CyberCloud CallController is not a platform, not a suite, and not a programme you spend half a year rolling out. It is one app that does one thing completely: capture every phone call, turn it into text, and make it findable in seconds on what was said.
Small in what you see. Complete in what it covers.
Small, and complete precisely because of it
Software that touches voice data almost always grows large: a recording platform, an archive system, a search engine, a reporting layer, and an integration project to tie the four together. Every seam is a place where data gets stuck and somebody has to own it.
CallController skips that step. Recording, transcription, search and reporting sit in the same app, on the same data. There is nothing to integrate, because there is nothing to pull apart.
Transcription does the boring work
Every call goes through transcription automatically. Nobody has to listen, label or summarise — the text is there the moment the call ends.
That is the step that makes the rest possible. As long as an archive is made of audio files, it is a pile. The moment it is made of text, it is an index.
Searching audio as if it were just text
You can search along three lines: who called, who answered, and what was said. The third one is where it gets interesting.
A word spoken in a call eight months ago is on your screen within a second — not because somebody tagged it at the time, but because everything is searchable by default. Anyone who has ever scrubbed through half an hour of audio hunting for one sentence knows exactly what that is worth.

Seeing what actually happens in your calls
On top of the individual calls sits an analytics layer: how many calls come in, what share gets answered, what they are about, how they end, which hours peak and who calls most often.
No separate BI track, no nightly export into a dashboard tool. The same data, one screen further.

Scaling is no longer a project
The heavy steps — transcribing, analysing, indexing — run on cloud technology that moves with the load. A thousand calls a month or a hundred thousand makes no difference to the app.
That is exactly what the cloud is good at, and what this app leans on hardest: growth needs no migration, no extra servers and no redesign. The difference shows up on the invoice, not in the architecture.
Open source, so not a black box
The foundation is open source. You can see what happens to your voice data, adapt the app to your own situation, and you do not depend on a single vendor to reach your own archive.
For data you have to keep for years, that weighs more than it does for software you will replace within three anyway.
And compliance? That comes along for the ride
If your organisation falls under MiFID, PCI DSS or SOX, you have to retain calls, demonstrably, and produce them on request. In CallController, retention periods and access rules are configuration: the system enforces them, nobody has to remember them. In an audit that is the difference between demonstrating and promising.
But it is not the reason to want this app. It is what you get once your archive is searchable.

That is the heart of this case: one small app, built entirely on what the cloud does well, turning a mandatory archive into something you actually use every day.
What CyberCloud Voice Analytics looks like
A few screens from the product, as you see them in use.

We're confident we can supercharge your software operation
Our products and services will delight you.
AI engineering
Use AI where it genuinely helps, with accountability staying with people.
Read more:

What you're missing with AI agents is rarely a tool
I have been running several AI agents side by side for months. After five hours of DHH on programming with agents, my to...

The creator of Ruby on Rails doesn't write code any more
The creator of Ruby on Rails no longer writes a line of code himself and drives sixteen agents at once. Five hours with ...

AI Vampires: The Hidden Price of Twenty Agents
On Joe Rogan, Marc Andreessen describes a new kind of programmer: one who stops sleeping because twenty agents are waiti...

Bug Fixing in the Age of AI: How to Use Coding Agents Without Turning Your Codebase Into Spaghetti
Bug fixing has changed. Not because bugs are different. They’re still null references, race conditions, broken assumpti...

AI Fatigue in Development: Why Constant AI Assistance Can Wear You Down
There’s a familiar pattern among developers who have spent any time with AI-assisted tools: initial curiosity, followed ...

AI-Assisted Code Reviews: What the Latest Research Reveals About GPT in Pull Request Workflows
At ZEN, we keep a close eye on emerging research that affects how engineering teams build, ship, and maintain software. ...



