LLM behavioral analysis
A fine-tuned language model scores each session's action sequence — navigation rhythm, dwell time, interaction entropy — the way an analyst would, at machine scale.
LLM-powered detection engine — now generally available
Phylaxa uses large-language-model behavioral analysis to distinguish humans from automation in real time. Block scrapers, credential stuffing and fake-account fraud — with zero CAPTCHAs and under 5 ms of added latency.
Deploys at the edge in minutes · No user friction · SOC 2 aligned
Modern bots mimic browsers, rotate residential IPs and solve CAPTCHAs. Phylaxa counters them with a detection stack that reasons about behavior, not just signatures.
A fine-tuned language model scores each session's action sequence — navigation rhythm, dwell time, interaction entropy — the way an analyst would, at machine scale.
300+ passive signals across TLS, HTTP/2, canvas and runtime behavior identify emulators, headless frameworks and replayed sessions without invasive scripts.
Legitimate users never see a puzzle. Risk is scored silently in the background, so conversion stays intact while automation is turned away.
Every request receives a 0–100 risk verdict in under 5 ms at the edge, with allow, monitor, throttle or block actions enforced inline.
Detection models retrain continuously on attack traffic observed across the network, closing the gap when bot operators change tactics.
No third-party cookies, no cross-site tracking, regional data residency and GDPR/CCPA-aligned processing by default.
Everything you expect from a top-tier bot mitigation platform — built LLM-native from day one.
What changes when detection goes inline at the edge.
Global airline
92% of login traffic was credential-stuffing bots.
Leading e-commerce platform
A 13-day scraping campaign sent 80 million requests — all absorbed at the edge.
Streetwear retailer
Scalper bots targeted every limited drop.
Anonymized results from representative customer deployments.
Straight answers about how Phylaxa detects bots, deploys and protects user privacy.
Phylaxa is an AI-native bot management platform that protects websites, mobile apps and APIs from automated abuse — including web scraping, credential stuffing, account takeover and fake-account creation — using large-language-model behavioral analysis instead of CAPTCHAs.
Phylaxa scores every session silently. It combines a fine-tuned language model that reasons about session behavior with 300+ passive device, network and TLS signals. Human users pass through with no puzzle, while automated traffic receives throttle, challenge or block actions.
Most teams deploy Phylaxa in under an hour. Edge connectors exist for major CDN and cloud platforms, plus lightweight server SDKs and a JavaScript agent. No DNS change or traffic rerouting is required for monitor-mode evaluation.
Median inline scoring latency is under 5 milliseconds at the edge. Phylaxa runs on a global anycast network, so decisions happen close to your users without adding a network hop to your origin.
Yes. Phylaxa is privacy-first by design: it uses no third-party cookies and no cross-site tracking, supports regional data residency, and processes only the signals required for detection. Processing agreements and audit documentation are available under NDA.
Traditional bot managers rely on static rules, IP reputation and JavaScript challenges that modern bots increasingly bypass. Phylaxa replaces rule tuning with a continuously retrained LLM detection engine that adapts to new attack tactics without manual signature updates.
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