ARGUS - Executive Summary¶
AI-Powered Autonomous E2E Testing Platform
The Problem¶
Engineering teams spend 80% of QA time on test maintenance, not actual testing. Every UI change breaks selectors, tests are slow to create, and flaky tests erode confidence. Traditional tools don't understand your codebase—they only see the DOM.
The Solution¶
Argus is a fully autonomous testing platform that generates tests from plain English and self-heals broken tests. Works with zero code access (90-95% healing) or with optional git integration for 99.9% accuracy.
Deployment Options¶
Git-aware healing is OPTIONAL. Argus works with zero code access.
| Mode | Code Access | Healing Accuracy | Best For |
|---|---|---|---|
| DOM-Only | None required | 90-95% | Privacy-first, quick POCs, agencies |
| Git-Aware | Read-only | 99.9% | Teams wanting maximum reliability |
| Self-Hosted | On-premise | 99.9% | Enterprise, regulated industries |
DOM-Only still includes: AI test generation, visual regression, multi-model savings, all 23 agents
Key Differentiators¶
| Advantage | What It Means | Impact |
|---|---|---|
| Flexible Deployment | DOM-only, Git-aware, or Self-hosted options | Works for any security requirement |
| Git-Aware Self-Healing | Reads git blame + source code (optional) | 99.9% accuracy vs 95% industry |
| Multi-Model AI Routing | Routes tasks to optimal LLM (Claude/GPT/Gemini) | 60-80% cost reduction |
| Full Codebase Understanding | Analyzes frontend, backend, database, and git | Tests that understand your app |
| Production Learning | Integrates Datadog/Sentry to prioritize tests | Real user impact drives testing |
| MCP IDE Integration | Works in Claude Code, Cursor, Windsurf | Tests where developers live |
Market Opportunity¶
| Metric | Value |
|---|---|
| Market Size (2024) | $856.7M |
| Projected (2032) | $3.8B |
| CAGR | 20.9% |
| AI Adoption | 60%+ enterprises by 2025 |
Platform Metrics¶
| Metric | Value |
|---|---|
| Codebase | 53,000+ lines Python |
| AI Agents | 23 specialized agents |
| Self-Healing Accuracy | 99.9% |
| Cost Savings | 60-80% vs single-model |
| Implementation | 65% complete |
Competitive Position¶
Self-Healing Multi-Model Flexible Production
Accuracy AI Deployment Learning
──────────── ─────────── ────────── ──────────
★ ARGUS 90-99.9%* ●●●●● ●●●●● ●●●●●
Applitools ~85% ○○○○○ ○○○○○ ○○○○○
testRigor ~90% ○○○○○ ○○○○○ ○○○○○
Mabl ~95% ○○○○○ ○○○○○ ○○○○○
Katalon ~90% ○○○○○ ●●○○○ ○○○○○
* 90-95% DOM-only (no code access) | 99.9% with git-aware (optional)
Business Model¶
| Tier | Price | Test Runs | Deployment Mode |
|---|---|---|---|
| Free | $0 | 100/mo | DOM-Only |
| Starter | $49 | 500/mo | DOM-Only |
| Pro | $99 | 2,000/mo | + Git-Aware |
| Team | $299 | 10,000/mo | + Git-Aware |
| Enterprise | Custom | Unlimited | + Self-Hosted |
Customer ROI: $150,000+ annual savings for mid-size teams (90% reduction in maintenance time)
Roadmap Highlights¶
| Timeline | Milestone |
|---|---|
| Q1 2026 | Public beta, Gemini integration, hybrid DOM+Vision |
| Q2 2026 | Enterprise SSO/RBAC, production monitoring |
| Q3 2026 | Custom LLM fine-tuning, mobile native testing |
Why Now?¶
- AI testing mainstream - 60%+ enterprise adoption by 2025
- LLM costs dropping - Gemini Flash at $0.10/M tokens (90% YoY decrease)
- Competitors stuck - Still DOM-only, no codebase awareness, cloud-only deployment
- First mover advantage - Only platform with git-aware healing AND flexible deployment options
The Ask¶
Seeking strategic partners and early adopters to: - Validate product-market fit with design partners - Scale infrastructure for enterprise workloads - Expand go-to-market capabilities