Our Mission & Roadmap

Our Mission

To teach machines to hear, and to give every human a voice in AI.

Silencio is building the audio layer of artificial intelligence: a global, people-powered network that captures real-world voice and sound, with consent, in every language the world speaks. We exist to close the two gaps that define this era of AI, the nearly four billion people it cannot understand, and the physical world it cannot perceive. Every voice we capture advances both at once: it is training data for the machines of the next decade, income for the person who gave it, and a permanent record of a way of speaking that might otherwise disappear.

We measure success in three numbers: the languages and dialects AI can hear because of us, the people earning from the value of their own voice, and the share of the world's voice AI trained on data our network supplied. The mission is complete when nothing human is unheard.

Roadmap

From proving the network to owning the audio vertical.

Each phase of Silencio exists to prove one thing. The first proved that a planetary-scale, consent-based data network can be built from ordinary smartphones. The second proved that this network produces revenue-grade voice data that the world's most demanding buyers will pay for. The phases ahead scale that proven engine toward a single position: the default audio data infrastructure for AI and robotics.

2022 - 2023 Proving the network Silencio launches and grows into the world's largest noise level data bank, contributors in nearly every country measuring the sound of their world. The lasting result is not the noise data. It is the proof that millions of people, across 180 countries, will contribute real-world data with consent, the single hardest precondition of everything that follows.

2024 Proving the economics The network passes its first revenue, launches verifiable on-chain consent and rewards, and demonstrates the loop that defines the model: data revenue flowing back into the network that produced it.

2025 - 2027 The pivot to voice, and the push to own it Silencio turns its network in full toward the defining data gap in AI. Voice collection goes live across scripted speech, natural conversation, and command data, with human transcription and validation. The network spans more than 2.5 million contributors, over 1,000 languages and dialects, and an off-the-shelf catalogue exceeding 500,000 hours, with frontier AI labs and Fortune 100 companies already training on data sourced from it.

The mandate for this phase is aggressive and specific: close the next wave of frontier labs and Fortune 100 clients, push the token flywheel hard so that every dollar of data revenue tightens supply and rewards the network that earned it, and pursue every niche language on earth, the rare and low-resource tongues that competitors cannot reach and AI cannot do without. The network itself scales with the demand it serves: from 2.5 million contributors to 10 million, then 50 million, each step widening coverage and dropping the cost of the next dataset.

The same period opens the second front: embodied AI. The contributor network begins capturing egocentric, first-person data, the sound and context of the world as a person moves through it, which is precisely the data the coming generation of robots and agents must train on. This is the deepest layer of the moat: the community is the asset, and the asset is retargetable. A network of millions of consenting contributors can shift from one dataset type to the next in weeks, at a marginal cost no studio, vendor, or sensor fleet can approach. Whatever data AI needs next, Silencio is already standing where it has to be collected: everywhere, faster and cheaper than anyone.

The destination does not move. Silencio becomes the infrastructure other companies build on: the first place any lab, enterprise, or robotics company comes when a machine needs to hear, and the standard for how real-world data is sourced ethically at scale. The long arc is unchanged and unhurried: a world where every machine that listens, and every person who speaks, passes through the network we are building now.