Agent Lisa provides an AI‑driven security layer that scores inbound HTTP requests at the edge to differentiate human users from bots in real time. It integrates via CDN routing or lightweight SDKs, applying adaptive challenges only when confidence is low, and offers a centralized dashboard for policy management and analytics.
Funding
Funding not disclosed
Founders
Product
Problem
Websites increasingly face automated bot traffic that can scrape content, launch credential‑stuffing attacks, or inflate analytics, leading to degraded performance, higher infrastructure costs, and security breaches. Traditional rule‑based defenses often generate false positives or require manual tuning, making it difficult for operators to maintain a seamless user experience while blocking malicious requests.
Solution
Agent Lisa delivers an AI‑driven security verification layer that intercepts inbound HTTP requests at the edge and evaluates each interaction against a continuously trained behavioral model. The service distinguishes legitimate human sessions from automated bots in real time, allowing only verified traffic to reach the origin server. Integration is achieved via lightweight SDKs or DNS‑level routing, eliminating the need for on‑premise hardware. When uncertainty exceeds a confidence threshold, the platform can present an adaptive challenge (e.g., invisible CAPTCHA) before granting access. All verification decisions and telemetry are streamed to a centralized dashboard for monitoring, policy adjustments, and compliance reporting.
Target Audience
The primary customers are e‑commerce operators, SaaS platforms, online publishers, and any web‑facing service that requires high‑availability protection against automated abuse while preserving a frictionless user experience.
Features
- Real‑time request scoring using deep‑learning models trained on millions of bot and human interaction patterns
- Edge deployment via CDN integration to minimize latency and offload traffic before it reaches origin servers
- SDKs and API endpoints for seamless integration with web frameworks, serverless functions, and load balancers
- Adaptive challenge mechanism that escalates to invisible or visible CAPTCHAs only when confidence is low, preserving user experience
- Granular policy engine supporting IP reputation, rate limiting, and custom rule sets for fine‑tuned mitigation
- Centralized analytics console with dashboards for bot traffic trends, false‑positive rates, and compliance audit logs
- GDPR‑compatible data handling with anonymized fingerprinting and end‑to‑end encryption of telemetry
- Auto‑scaling architecture that adjusts processing capacity based on traffic spikes without manual intervention