Introducing PRISM
PRISM is a desktop application for detecting and humanizing AI-generated text. It runs locally, analyzes offline, and gives you control over how your writing sounds.
The problem
AI-generated text has a signature. Uniform sentence lengths. Predictable transitions. Hedging language. Corporate jargon. No personality, no voice, no humanity.
The problem isn't that people use AI to write. The problem is that AI-generated text is identifiable — and nobody has good tools to understand why or where in their text the signal shows.
Writers need to know if their drafts sound robotic. Editors need to spot AI-assisted submissions. Professionals need to polish AI-drafted content without sounding like a machine.
The existing detection tools are cloud-based black boxes. You paste your text into someone else's server, get a percentage back, and hope they're not training on your content.
The approach
PRISM analyzes text locally using a combination of heuristics and machine learning.
| Cloud Detectors | PRISM |
|---|---|
| Text uploaded to external servers | Everything runs on your machine |
| Black box score, no explanation | Sentence-level heatmap with reasons |
| Subscription for basic features | Open source, MIT licensed |
| Single language, usually English | English, Italian, Spanish, German |
Perplexity, burstiness, entropy, and pattern matching work together to produce an AI probability score. A sentence-level heatmap shows exactly which parts triggered detection and why.
Two modes
Detect
Paste text. View the AI probability score and metrics. See a color-coded heatmap highlighting which sentences triggered detection. Click humanize for three style variations — Natural, Creative, Professional.
Compose
Write rough text in any language. Select source and target language. Get three polished versions with distinct voices. Copy the one that fits. Repeat and refine.
Architecture
Built with Tauri 2.0 — a lightweight Rust-based desktop framework. The React frontend handles UI and state management through Zustand, while all analysis runs natively in Rust.
Text analysis combines ONNX-based machine learning inference with heuristic metrics. The Claude API provides humanization when configured. API keys are stored in the OS keychain — never in config files.
The design decision that shaped everything: local first.
Detection runs entirely offline through ONNX Runtime. No internet required. No data leaves your machine. Humanization can use the Claude API for the highest quality, or local ONNX models for complete offline operation.
Why open source
A detection tool that isn't transparent about its methods isn't a detection tool. It's an oracle asking you to trust it.
PRISM is MIT licensed. The detection logic, the heuristic weights, the ML model — all visible, all auditable. If you disagree with how we score text, you can see exactly why and adjust it.
This matters because AI detection is inherently probabilistic. No tool is 100% accurate. The least we can do is show our work.
Where we are
PRISM is functional and open source on GitHub. The detection engine is stable. Humanization works through both Claude API and local ONNX models.
Active development continues on detection accuracy and language expansion.
What's next
Better models, more languages, sharper heuristics. The goal is a tool that helps you write with AI without losing your voice.
See through synthetic text. Write through it.