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UVERA

About us

We build AI that pauses, explains, and lets people decide.

UVERA (from Latin vera, “true”) is a trust layer for mobile money in Bangladesh, built by the UVERA team for AI DEV FEST 2026, Track 07.

01

Why

A scam transfer finishes in seconds. The people it hurts are often new to digital money, and nobody asks them to pause.

02

How

Seven AIs on a seeded synthetic world of 2.2 million events. Each one is compared with a simpler baseline and tested on people it never saw.

03

Principles

Never block. Say “not sure” when unsure. Show the evidence. A person approves every hold, and every number comes from a notebook run.

0

hours to build

0

Kaggle notebooks

0

AI components

0M

synthetic events

0

real customer records used

How it came together

Seventy-two hours, in order.

Day 1

A world to learn from

We built a seeded synthetic world: 20,000 customers, 600 agents, 2,500 shops and 120 days of activity, with hidden scam processes, honest look-alikes, label noise and a leakage guard.

Day 2

Seven AIs, nine notebooks

Every model ran on Kaggle against a baseline: grouped cross-validation, calibration, conformal “not sure”, exact TreeSHAP reasons, rolling forecasts and a grounded Gemini brief with a validator.

Day 3

One website for everyone

Customer, agent and operations areas on a live API, a Trust Center that reads the notebook results, and this 3D field drawn from the same synthetic world.

7 Oct

The on-site final

A live demo, the report and the evidence, side by side.

The team

Three people, one weekend.

Portrait of Tanvir Hossin

Tanvir Hossin

Team lead & design

Leads the team, the product story and the visual design.

Portrait of Abdullah Rubab

Abdullah Rubab

Lead AI/ML & development

Machine learning, the website and the API: synthetic world, Pause Check, briefs and evaluation.

github.com/ABRUBAB
Portrait of Abdur Rahman

Abdur Rahman

Backend & AI/ML

Backend services and model notebooks.

Honest by default

What this is, and what it is not.

  • All people, wallets, shops and messages are synthetic. Results show that the method works, not real-world accuracy.
  • This is an independent hackathon prototype. It is not affiliated with, or endorsed by, any payment provider, and it describes no provider's internal problems.
  • Every external dataset, model, API and component is listed with its license in the repository.
  • Want the evidence? Open the Trust Center.