ZeroSweep ⚡

September 18, 2026 · View on GitHub

A high-performance benchmark and architectural showcase demonstrating why System One Models (TypeSafe AI's Jev) beat autoregressive LLMs at triage and email workflows.

Built with Next.js Powered by TypeSafe TypeScript Tailwind CSS

🎯 The Core Thesis: The System-One Architecture Shift

Running thousands of emails, support tickets, or security logs through a traditional 70B+ autoregressive LLM (GPT-4o, Claude 3.5 Sonnet) is an architectural anti-pattern:

  1. Unacceptable Latency: 2,000ms – 30,000ms per item due to sequential token-by-token decoding (O(N) forward passes).
  2. Economic Insolvency: Output tokens cost ~5x input tokens ($15–$40 per 10k emails).
  3. Overconfidence & Schema Drift: Models output authoritative text even when hallucinating formats or misidentifying ambiguous edge cases.

TypeSafe Jev replaces autoregressive string generation with a single-pass parallel sampler (O(1)) trained via RLCD (Reinforcement Learning for Calibrated Decisions):

  • ⚡ 100ms Responses: 40x to 150x faster execution.
  • 💰 $0.042 / MTok Input: Output tokens are $0.00 (Free / too cheap to meter).
  • 🛡️ Epistemic Calibration: Calibrated confidence scoring enables safe Negative Engineering (ambiguous items trigger human review rather than false-positive destruction).
  • 🔒 Zero Format Errors: Natively evaluated at the logit layer—mathematically impossible to return malformed JSON.

🚀 Key Features

1. ⚡ Autonomous "Inbox Zero" Mailbox (1,000+ Scale Client)

  • A full-fledged, high-density 3-pane webmail interface (Superhuman / Linear grade).
  • Scale Dataset Selector: Choose between 50, 250, 500, or 1,000 procedurally generated realistic emails.
  • 4-Worker Concurrent Streaming Batch Queue: Sweeps emails using TypeSafe Jev in parallel streaming batches ($0.042/MTok, $0 output tax) with a live streaming HUD tracking throughput (~45–90 emails/sec), elapsed time, and total cost.
  • Smart Folders with Live Badges: All Mail, Needs Action, Human Review (Safety Gate <85%), Newsletters, Receipts & Tax, System Alerts, and Trash Quarantine.
  • 1-Click "Purge Trash": Permanently sweeps all quarantined spam/phishing with an animated clean slate celebration to reach Inbox Zero.
  • Embedded Jev Telemetry Card: Inspect choice probabilities, calibrated confidence, noul scores, and verified Envoy gateway latency in the reader pane.

2. 🧪 1-Email Precision Lab & Speedometer Diff

  • Type or paste any custom email (From, Sender Name, Subject, Body) or choose from 6 realistic instant presets (P0 Outage, Term Sheet, Spear Phishing, Stripe Receipt, etc.).
  • Granular Model Triggers:
    • ⚡ "Analyze with Jev": Real-time parallel sampler (~70–180ms) returning typed category, logits, and calibrated confidence.
    • 🤖 "Analyze with LLM": Real-time autoregressive model via OpenRouter (~4,000–6,500ms) with live running stopwatch.
    • ⚡🤖 "Race Both Head-to-Head": Launches both simultaneously to visually observe the 35x+ compute speedup.
  • Generates ready-to-use cURL commands with x-envoy-upstream-service-time extraction pipes for direct terminal verification.

3. 🏁 The 10-Email Head-to-Head Race Arena

  • Side-by-side execution timer, token meter, and cost ticker.
  • Evaluates 10 emails in parallel with Jev in ~220ms ($0.0004) vs 22,000ms ($0.065) with an autoregressive LLM.

4. 🔬 The Epistemic Calibration Inspector

  • Explains how Jev's RLCD training produces mathematically calibrated confidence scores:
    • Confidence ≥ 0.85: Verified high-confidence automated triage.
    • Confidence < 0.85: Negative-engineering safety gate overrides deletion and dispatches to Human Review.

5. 📊 Enterprise Unit Economics Calculator (Live Market Rates)

  • Interactive volume slider (10,000 to 10,000,000 emails/month).
  • Interactive commercial model tier switcher aligned with live OpenRouter market rates:
    • Frontier Flagship: OpenAI GPT-6 Astra / Claude Fable 5.1 ($10.00 in / $50.00 out)
    • Workhorse Pro: Claude Opus 5 / GPT-5.6 Sol Pro ($3.50 in / $17.50 out)
    • High-Speed Flash: Google Gemini 3.8 Flash ($0.75 in / $3.75 out)
    • Budget Open-Weights: DeepSeek V4.1 Flash ($0.15 in / $0.60 out)
  • Mathematical pricing breakdown proving how Jev eliminates the 4x–5x output token tax ($0.042/MTok in, $0.00 out).

6. ⚡ True Latency Decomposition Telemetry

  • Cluster Compute vs Public Transit: Direct extraction of TypeSafe's x-envoy-upstream-service-time header from its Istio/Envoy service mesh.
  • Viewers immediately see:

    ⚡ 72ms Model Compute + 🌐 140ms Network Transit = 212ms Total Wall-Clock

  • Proves that Jev evaluates email intent faster than light travels across the Atlantic ocean, contrasted against autoregressive LLMs which spend 5,000ms+ sequentially decoding tokens on GPU.
  • Includes 1-click Share Benchmark summary generator for technical reviews.

7. 🛡️ Zero-CORS Secure Backend Architecture

  • Completely eliminates client-side CORS errors and browser key-leakage risks.
  • All requests are executed server-side via Next.js App Router handlers (/api/triage/typesafe, /api/triage/typesafe/batch, /api/triage/llm).

🛠️ Tech Stack & Architecture

  • Framework: Next.js 14 (App Router, React 18, TypeScript)
  • Styling: Tailwind CSS (Linear/Vercel dark-mode telemetry aesthetic)
  • Icons: Lucide React
  • Engine Adapters:
    • src/lib/typesafe.ts: Live TypeSafe HTTP gateway client + Envoy telemetry extraction.
    • src/lib/llmBenchmark.ts: Frontier autoregressive comparative baseline.
    • src/lib/safetyGate.ts: Epistemic thresholding logic (confidence < 0.85 -> Human Review).

📦 Getting Started

Local Development

# 1. Clone the repository
git clone https://github.com/sysadarsh/zerosweep.git
cd zerosweep

# 2. Copy environment file and configure keys
cp .env.example .env.local

# 3. Install dependencies
npm install

# 4. Start development server
npm run dev

Open http://localhost:3000 in your browser.

Production Build

npm run build
npm run start

🚢 Deploy to Vercel (1-Click Deployment)

Deploy your own live ZeroSweep instance directly to Vercel with zero configuration:

Deploy with Vercel

Required Environment Variables

When deploying on Vercel, simply configure two environment variables in your project settings:

VariableRequiredDescriptionWhere to Obtain
TYPESAFE_API_KEYYesTypeSafe AI System One API Keyapi.typesafe.ai
OPENROUTER_API_KEYYesOpenRouter API Key (for comparative baseline)openrouter.ai/keys

🔒 Security Notice: All API requests are proxied server-side via Next.js 14 App Router API handlers (/api/triage/*). Your private API keys are never exposed to the client browser, and the backend strictly locks comparative LLM requests to the free DeepSeek Flash model to guarantee zero accidental spend.

👨‍💻 Author & Connect

Adarsh — Autonomous Systems Engineer

🤝 Acknowledgements & TypeSafe Resources

📄 License

MIT License. Created to demonstrate the power of TypeSafe AI's System One architecture.