SydeLabs provides automated red teaming and real-time intent-based protection to identify vulnerabilities and prevent attacks on AI systems. The platform ensures compliance with evolving regulatory requirements, enabling businesses to securely deploy AI applications without risk blind spots.
Funding
$2.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.



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Founders
Product
Problem
AI systems are vulnerable to novel attacks and abuse, creating risk blindspots that hinder secure deployment. Organizations lack a defined approach to identify and address these vulnerabilities, while the absence of real-time protection measures leaves AI deployments susceptible to emerging threats. Furthermore, an evolving regulatory landscape around AI usage creates compliance risks and potential business continuity issues.
Solution
SydeLabs offers a comprehensive AI security and risk management platform that preempts vulnerabilities and provides real-time protection against attacks and abuse. The platform utilizes automated red teaming to identify vulnerabilities in AI systems through ongoing assessments. It also employs real-time threat scoring to proactively prevent attacks across multiple categories, establishing a robust defense for AI systems. SydeLabs helps organizations understand detailed gap assessments of their AI systems across multiple regulatory and compliance requirements.
Target Audience
The primary customers are businesses deploying AI applications, particularly those using LLMs, who need to ensure security, prevent abuse, and maintain compliance.
Features
- Automated AI red teaming for continuous vulnerability discovery
- Real-time intent-based protection to prevent attacks and abuse
- Dynamic compliance gap assessment to meet evolving regulatory requirements
- Seamless integration with models such as Claude, GPT, Gemini, and proprietary LLMs
- Real-time threat scores to proactively prevent attacks