OmniAI

Hi, we're OmniAI.

Nobody starts a business to retype spreadsheets.

We're two engineers from Fudan University in Shanghai. We build the software and AI that take repetitive work off your team, and we stay to keep it running after launch.

  • built for
  • a scrap-steel trader in Indonesia
  • welding robots in Shanghai
  • family budgets on three phone platforms
  • a school group with 15+ campuses
  • a college in Florida
  • a home-furnishing platform

A lot of good businesses still run on spreadsheets, chat messages and one person who remembers everything. We turn that into simple, sturdy software, and we add AI only where it gives your people their hours back.

Indonesia, steel trading

A thousand truckloads a month, each one typed once.

Every truck that crosses the weighbridge at an Indonesian scrap-steel trader comes with a ticket: supplier, smelter, gross and net weight. That ticket used to be retyped into separate Excel files for invoices, payments and tax, and month-end meant checking them against each other by hand.

Feroxa ERP lets the team enter the ticket once. The invoice, the receipt, the Coretax tax file and the supplier statement all come from that one entry. When something breaks, an AI agent finds the bug, writes a fix and tests it within minutes, and a person approves it before it goes live.

1,000+load tickets a month
3–12 minfrom a bug to a tested fix
323automated tests guarding it

Illustration with sample data

Shanghai, industrial robots

Every weld, on the record.

A Shanghai maker of mobile welding robots needed proof of every seam: current, voltage, speed and weave, sent up to a cloud platform. The catch was that the software could look at the robot, but never touch its controls.

The app sits on the robot's industrial PC. It reads the welding data, flags anything doubtful, and serves it to the data box that uploads it. It reconnects and restarts on its own, so it can run around the clock without anyone watching it.

0errors in 3,557 site responses
371automated tests
24/7runs on its own
焊接数据采集与上传系统 V1.1.3
Screenshot of the welding data table: welding on, current 180 A, voltage 24 V, speed 300 mm/min and weave settings, every row marked normal.

the real screen. 正常 means every value checked out.

China and beyond, family money

Say what you spent. It writes it down.

Typing in every expense is the part of budgeting people give up on. In Monezi you just say it: takeaway 30, taxi 20. The app hears it, splits it into entries, sorts them into categories and waits for a quick confirm. Snap a long receipt and it reads that too.

Leonardo built it end to end as full-stack engineer: the iPhone, Android and HarmonyOS apps, plus the server, sign-in, payments and the AI behind it, which runs on different models for mainland China and abroad.

3platforms: iPhone, Android, HarmonyOS
1sentence is enough to log several expenses

Indonesia and Florida, education

Thousands of students, fewer forms.

At Pelita Harapan Group, Alfin led the development team behind the systems its campuses relied on: online admissions, inventory and facility management, and a Moodle learning platform. Admissions handled more than 4,500 applications a year, and the inventory system kept track of over a billion rupiah in assets.

Before that, at Pensacola Christian College in Florida, he built a course recommendation engine that cut student enrollment errors by 80%, and rebuilt the college's graduation management system.

Fudan University, AI research

We study how AI agents break.

AI agents look great in a demo and then fail in strange ways in real use. Alfin's research is about exactly that. He built a pipeline that collected 201 real bug reports from AI agent projects and reproduced 50 of the failures, so fixes can be tested properly. The work was published at NeurIPS 2025, one of the top AI research conferences, with Alfin as co-first author.

It's the same instinct behind the bug-fixing agent in Feroxa ERP. AI only helps a business if it keeps working after the demo.

201real agent bug reports studied
50failures reproduced

NeurIPS 202539th Conference on Neural Information Processing Systems

Can Agents Fix Agent Issues?

Alfin Wijaya Rahardja*, Junwei Liu*, et al.
* equal contribution

Introduces AgentIssue-Bench, built from real issues in AI agent systems, each reproduced in its own environment so that fixes can be checked automatically.

and plenty more

Other things we've made

An AI that furnishes a room with you

Upload a floor plan, get a 3D room and furnish it with real products by chatting. The agent remembers your style and budget, and a layout checker stops it from blocking doors.

Leonardo, at Shanghai Maxo

Photo to CAD for welding robots

Turns photos of metal parts into editable CAD models that help the robot's vision system find each part's exact position. Tested on 1,418 real samples.

Leonardo, Fudan lab project

Floor plan to 3D, in a weekend

A prototype that turns a floor plan image into textured 3D rooms, built over one weekend to bring something real to an interview.

Leonardo

Point of sale and inventory

A POS with stock management for retail, and a restaurant POS for orders, tables and payments.

Alfin

StudyReserve

A full-stack web app for booking study seats and classrooms, plus an online exam maker for building and running tests.

Alfin

AiSpea

Turns a child's conversations with a smart toy into growth reports for parents. Reached the national top 16 of the 2025 Global AI Innovation Competition.

Leonardo, team lead

sounds familiar?

How we can help

If one of these sounds like your business, here is what we would build for it.

We type the same numbers into five different places.

One system for your operations

ERP, point of sale, inventory, admissions or bookings. Data goes in once, and invoices, reports and tax files come out of it.

We know AI could help. We just don't know where to start.

An honest AI assessment

We look at how your team works, show where AI saves real hours, what it costs to run, and what to build first. You keep the plan either way.

Half our day goes to reading documents and chasing messages.

AI assistants that do the filing

Assistants that read documents and receipts, understand voice, answer from your own data, and hand their work to your systems for a person to approve.

Our customers keep asking for an app.

Mobile and web apps

iPhone, Android and HarmonyOS apps with the server, sign-in, payments and admin tools behind them, ready for Chinese and international app stores.

Our machines produce data that nobody ever sees.

Industrial data and 3D

Software that safely reads data from robots and machines and puts it where people can use it, plus 3D models from photos and floor plans.

Our AI feature worked in the demo. Real customers broke it.

AI testing and reliability

Test sets, monitoring and fixes for AI features, from the people who published research on how AI agents fail.

no surprises

What working with us looks like

  1. 1

    We learn your work

    We talk to the people doing the job and collect the spreadsheets, forms and odd cases that make it hard.

  2. 2

    You try it early

    You get something you can click through, using your real data, while changes are still cheap.

  3. 3

    We build it properly

    Automated tests and release checks on every change, so new features don't break old ones.

  4. 4

    We stay after launch

    Error alerts, user and operations manuals, and fixes when something needs attention.

AI drafts.
People approve.

That's our rule for every AI feature we ship. The agent in Feroxa ERP writes fixes, but a person approves each release. Monezi suggests entries, but you confirm them. The welding software can read the robot, but it can't move it.

the two of us

Meet the founders

Alfin Wijaya Rahardja

Co-founder · enterprise systems and AI reliability

Alfin spent seven years in Florida, first studying computer information systems and then building systems for Pensacola Christian College. He went on to lead the development team at Pelita Harapan Group in Indonesia, serving more than 15 campuses. Now at Fudan University, he researches how to make AI agents reliable, and was co-first author of a NeurIPS 2025 paper on it.

seven years in Florida, now building in Shanghai

MS Electronic and Information Engineering, Fudan University, 2024 to 2027, Chinese Government Scholarship

BS Computer Information Systems, Pensacola Christian College, 2013 to 2017

Leonardo

Co-founder · product engineering, AI agents and 3D vision

Leonardo is doing his master's in artificial intelligence at Fudan University, after a bachelor's in AI at Northwestern Polytechnical University, where his thesis on 3D reconstruction was named one of the university's Top 100. He is the sole developer of Feroxa ERP, built the welding robot data system, and was the full-stack engineer on Monezi.

former president of his university's chess club

MEng Artificial Intelligence, Fudan University, 2025 to 2028

BEng Artificial Intelligence, Northwestern Polytechnical University, 2021 to 2025

we speakEnglishBahasa Indonesia中文

so, what eats your team's week?

Tell us the one task your team would happily never do again.

We'll come back with how we would approach it and what a first version could look like. We keep it in plain language, so you can judge it for yourself.

Fastest

Reply to the email that brought you here

It comes straight to one of us.
Alfin

linkedin.com/in/arahardja

Enterprise systems, AI reliability
Leonardo

linkedin.com/in/leonardo-fudan

Product, AI agents, 3D