Palaver AI

Palaver AI.

The core models and APIs underneath everything: language understanding, generation and agentic tasks across African languages.

In development Concept stage. Details may change as we build.

A young man showing a phone to a woman at a market stall full of pottery and fabric

What it is

Models that start with speech.

Most African languages lack the text that conventional language AI depends on. Palaver AI is designed to learn from speech instead.

Models are trained end-to-end from audio to meaning to audio, which makes unwritten languages possible. During training, low-resource languages are upsampled so the widely spoken ones don't drown them out.

Palaver AI is the foundation Palaver Voice and every later application will be built on, and it's planned as APIs that others can build on too.

How it learns

A curriculum, spoken aloud.

Parallel speech is collected from bilingual speakers in a structured order, each step adding a layer of the language.

  1. 1

    Word pairs

    Isolated word pairs for lexical alignment.

  2. 2

    Short phrases

    Phrases that carry prosody and basic syntax.

  3. 3

    Parallel narratives

    Full narrative texts for meaning and grammar.

  4. 4

    Audio to meaning to audio

    End-to-end training, so no written form is required.

Who it's for

Built for the people who must be reached.

  • Developers and platformsPlans call for APIs so products can understand and speak African languages.
  • Telecoms and banksVoice-first services for customers who aren't served by English- or French-only design.
  • InstitutionsMinistries and NGOs that need understanding, not just translation, in the field.
  • Palaver's own productsVoice, and every application after it, runs on the same models.

What's coming

The road ahead.

Where we're headed. These are plans, not shipped features.

  1. Near term

    Speech-to-speech for the first 50 languages

    High-quality speech-to-speech for an initial set of 50 languages, measured on held-out parallel data.

  2. Mid term

    Streaming and dialects

    Streaming inference with sub-second lag for conversation, dialect robustness, and pipelines that generate natural-sounding audio and simple video.

  3. Longer term

    Edge and agents

    Models that run on devices for ambient use, and agentic capabilities that complete multi-step tasks in local languages.

  4. Over time

    500+ languages

    Production-grade coverage of 500+ languages, with each new language getting cheaper to add as the data and modeling stack matures.

Need to reach people in the languages they speak?

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