CloakBrowser vs Kelet

CloakBrowser is an open-source stealth Chromium browser that defeats bot detection by patching fingerprints at the C++ source level — not through JavaScript injection or flag tricks that break on every update. With 49 C++ patches covering canvas, WebGL, audio, fonts, GPU reporting, screen properties, and WebRTC, it achieves 0.9 reCAPTCHA v3 scores (human-level) and passes Cloudflare Turnstile, FingerprintJS, and 30+ other detection systems out of the box. It's a drop-in replacement for Playwright and Puppeteer — swap one import line and your existing automation scripts work with zero other changes. An optional humanize=True flag adds Bézier-curve mouse movements, character-by-character typing, and realistic scroll patterns for behavioral detection evasion. Native SOCKS5/HTTP proxy support with GeoIP-matched locale makes multi-geo scraping seamless. With 7,800+ GitHub stars and 1,600+ gained today alone, it's clearly scratching a massive itch. The source-level patching approach means it survives Chrome version updates — a longstanding pain point that killed previous tools like undetected-chromedriver. It's fully open source, free to use, and auto-downloads its binary on first pip/npm install.

Kelet is a root-cause analysis agent for LLM applications that goes beyond trace visualization. Where most observability tools stop at showing you what happened, Kelet automatically reads your traces, cross-references failure patterns across thousands of sessions — thumbs-down ratings, abandoned conversations, LLM-judge flags — generates root cause hypotheses, and produces targeted prompt patches to address them. The workflow is: connect your traces (LangSmith, Langfuse, or direct API), let Kelet ingest your failure signals, and receive a prioritized list of failure clusters with explanations and draft prompt fixes. SOC 2 Type II certified, read-only access to traces — nothing is mutated. The indie team positions it as the missing "closing of the loop" in LLM observability: most teams can detect failures but have no systematic path from detection to fix. The HN thread surfaced a real pain point: teams know their chatbot is failing somewhere, but diagnosing which prompts, tools, or routing decisions are responsible requires manual trace archaeology. Kelet automates that archaeology and produces actionable output, not just dashboards.