Linh Ngo

I build AI systems that turn ideas into playable, watchable, shippable things.

My work sits where generative media, multiplayer games, multi-agent software, and privacy-preserving data systems meet. This page is the short version: active platforms, a live game, and a case study in making sensitive legacy data safer to evaluate and release.

Create with uncen.ai Play on multiplayers.ai Explore swiftest.ai Privacy and data safety

AI video studio

uncen.ai

Uncen turns a single prompt into short-form clips, long-form videos, music videos, narrated stories, scenes, voice, images, and assembled edits. It is the media engine underneath the rest of my work: workers coordinate the messy pipeline so creators can stay at the level of intent.

Prompt-to-video workflows for short and long form projects
AI images, voices, music, scenes, and editing/assembly tools
Worker orchestration designed for real production pipelines

Make something with uncen.ai

Vibe-coded multiplayer games

multiplayers.ai

Multiplayers.ai is built around a sharp thesis: vibe coding games should be multiplayer-first. Its games can leverage uncen.ai for images, audio, music, video, and world-building assets, then use swiftest.ai-style agents to design, critique, and iterate faster.

Generate, remix, copy, and publish browser games
Designed for multiplayer and shareable live demos from day one
Powered by uncen.ai media generation for art, sound, music, and richer worlds
Guided by smarter, faster, better agents inspired by swiftest.ai

Build a game on multiplayers.ai

Many minds AI

swiftest.ai

Swiftest.ai is my many-minds concept: a way to make AI work feel more like a team of specialized thinkers than a single chat box. The goal is better judgment, stronger iteration, and software that can carry complicated work across multiple perspectives.

Multi-agent reasoning, critique, and synthesis
Tools for evaluating ideas from several specialized angles
A product direction for faster, more thoughtful building

See the many minds idea

Playable demo

Rocket Boots, embedded from Multiplayers.ai.

This is the first version of the embeddable game widget idea: a live Multiplayers game running inside another webpage, with the same platform direction of AI-generated media from uncen.ai and agent-assisted iteration from swiftest.ai.

Portable embed

For the platform, this can become a generated widget snippet on every published game page.

<iframe
  src="https://crystal-signal-orbit.multiplayers.ai/?embed=1"
  title="Rocket Boots"
  allow="fullscreen; autoplay; gamepad"
  style="width:100%;aspect-ratio:4/3;border:0">
</iframe>

Music

Songs on Spotify

Music is part of the same practice for me: mood, pacing, structure, memory. These tracks sit next to the platforms because the worlds need sound as much as software.

Privacy and AI data safety

Data preparation that treats privacy as an engineering system.

Alongside creative AI and backend platforms, I design privacy-preserving pipelines for large legacy datasets. The work combines code-grounded visibility analysis, deterministic redaction, NER-assisted review, sensitive-content quarantine, media risk screening, and explicit release gates.

The case study below is based on internal DDN archive work. It is an engineering record, not a legal clearance opinion, and it does not expose row-level data.

Lineage and detection

Code-grounded lineage

Trace actual application visibility and access flags, validate schemas and joins, and distinguish content that is merely stored from content that is actually eligible for review.

Public versus private visibility semantics
Join and orphan-integrity checks
Direct-identifier and markup screening

Residual risk

Review before release

Automated detection is treated as a review signal, not as privacy clearance. Conservative NER and language signals feed a high-recall quarantine for sensitive or ambiguous material, with human validation gates.

Person, place, health, minor, and media-risk signals
Multilingual limitations documented
No buyer delivery until release gates pass

Evidence and governance

Aggregate-only release receipts

Reproducible runbooks, hashes, counts, and policy manifests make it possible to show what was checked without publishing source records, contact details, or row-level samples.

Approximately 8.96M posts and 9.79M postdata rows checked
Approximately 6.64M chat rows and 739,680 image rows profiled
247,220 forum records in strict internal validation

Discuss a scoped engagement

Earlier browser experiments

Before the current platforms, I spent years making little browser labs for simulation, compilers, neural networks, astronomy, film, and photography.

Exo-planet transit explorer C# Roslyn Deep Dream Image Painting Deep Q Learning Recurrent Neural Network Javascript AI Editor 2D Machine Learning Python & Turtle Graphics Film archive Photography archive