Sōli AI · Mobile

Soli Lite. Money intelligence that stays on the phone.

A small language model designed to run on an ordinary phone and turn the mobile-money messages people receive every day into clear, structured information, designed so their messages never leave the device.

In development Soli Lite has not been released. Its model card, evaluation results and downloads will be published on this page with the release.

The problem

Millions of people manage their money through text messages. Very few tools help them read those messages.

Every payment, transfer, loan and balance arrives as a short message, often in a mix of English, Swahili and Sheng. Understanding them, spotting a scam among them or keeping track of spending means reading each one by hand. Sending those messages to a cloud service to be analysed means handing over a detailed record of someone's financial life. Soli Lite is designed to do the reading on the phone itself, so the messages, and what they reveal, stay with their owner.

Design goals

What Soli Lite is being built to do.

01

Read the message

Turn a mobile-money message into structured facts: what kind of transaction, how much, with whom, and the balance after.

02

Stay grounded

Only report numbers and names that actually appear in the message. A model that invents an amount is worse than no model.

03

Run on the phone

Small enough to run on an everyday phone, so no message is sent anywhere to be understood.

04

Speak the language

Planned in stages: English first, then Swahili, then Sheng, each tested with material written by native speakers.

Where it stands

Published when proven.

We will only publish what we can show. Each item below appears on this page when it is real.

  1. Proof of conceptIn progress. Built on Qwen3-0.6B, an open model released by the Qwen team under the Apache 2.0 licence. Saolix is not affiliated with or endorsed by the Qwen team.
  2. On-device buildPlanned. Measured speed and memory on real phones will be published here.
  3. EvaluationPlanned. Results and method will be published with the release, with test sets where privacy and licensing allow.
  4. ReleasePlanned. Model card, licence terms and downloads.
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