SonnyLabs
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About
SonnyLabs provides a dedicated security layer for the modern AI stack, functioning as a real-time firewall for AI agents, chatbots, and Model Context Protocol (MCP) servers. Developed through proprietary research at University College Dublin, the platform is designed to intercept and neutralize malicious inputs before they reach large language models. This proactive approach prevents common vulnerabilities like prompt injections and jailbreaks, which can lead to unauthorized data access or unintended model behavior. By decoupling the security logic from the underlying LLM, the tool ensures that protective measures remain robust regardless of whether the organization uses OpenAI, Anthropic, or Meta’s Llama models. The technical implementation focuses on two primary performance profiles: speed and accuracy. The speed-optimized model is built for high-throughput, real-time applications where millisecond latency is critical, such as customer service chatbots. Conversely, the accuracy-optimized model provides deeper analysis, making it ideal for scanning complex documents and files where indirect prompt injections are harder to detect. Beyond simple input filtering, the system also monitors output to prevent the leakage of Personally Identifiable Information (PII) and confidential data, helping organizations maintain strict privacy standards and build customer trust in their AI deployments. This solution is particularly well-suited for security teams and developers in highly regulated industries, such as finance, legal, and government. With the rise of the EU AI Act, SonnyLabs offers a specialized path to compliance through automated risk assessment and gap analysis tools. This helps organizations avoid costly consulting fees while ensuring their AI systems meet European security standards. The platform’s versatility is reflected in its deployment options, allowing teams to integrate via a standard REST API or choose a self-hosted environment for maximum data sovereignty and control over their security infrastructure. What sets the tool apart is its specialized focus on the Model Context Protocol (MCP) and autonomous agents. While many security tools focus only on simple chat interfaces, this platform monitors multi-step reasoning paths and tool calls, detecting potential poisoning or context manipulation within complex agentic workflows. By providing a transparent audit trail and the ability to toggle between "Audit" and "Block" modes, it gives developers the flexibility to test security policies in development before enforcing them in production environments.
Pros & Cons
Developed through academic research at University College Dublin for high reliability.
Proprietary security models ensure data privacy by not relying on third-party LLMs.
Specialized protection for Model Context Protocol (MCP) infrastructure and AI tool calls.
Offers ultra-low millisecond latency options suitable for high-traffic chatbots.
Provides a dedicated training academy and automated tools for EU AI Act readiness.
Specific pricing for enterprise and compliance tiers is not publicly detailed.
The accuracy-optimized model involves higher processing time for deep analysis.
EU AI Act Academy and automated compliance tools require joining a waitlist.
Use Cases
Security engineers can implement a real-time firewall to block malicious prompt injections before they reach internal AI models.
Developers building autonomous agents can monitor tool calls to prevent unauthorized file access or context manipulation.
Compliance officers at European firms can use automated risk assessment tools to align AI applications with EU AI Act standards.
Customer service managers can secure public chatbots from jailbreak attempts while ensuring PII is never accidentally exposed.
Enterprises can use the self-hosted deployment option to maintain total data sovereignty while securing their generative AI stack.
Platform
Task
Features
• eu ai act compliance automation
• compatibility with openai, anthropic, and gemini
• self-hosted and api deployment options
• speed and accuracy optimized security models
• mcp server tool poisoning protection
• jailbreak attempt detection
• pii and confidential data leakage prevention
• real-time prompt injection blocking
FAQs
Does SonnyLabs integrate with AI agents and MCP servers?
Yes, it provides specialized security guardrails for both AI agents and Model Context Protocol (MCP) infrastructure. It monitors requests and tool calls to detect poisoning, context manipulation, and unauthorized sensitive file access.
How quickly can the security layer be integrated?
Integration is designed to be developer-friendly and can typically be completed in about five minutes. The service provides a straightforward REST API that works across various LLM architectures.
How is this service deployed?
SonnyLabs offers flexible deployment options to suit different security needs. You can use their hosted API for convenience or choose to self-host the solution to maintain complete control over your data.
How fast is the threat detection process?
The platform offers a speed-optimized model designed for ultra-low latency, ensuring security checks happen in milliseconds. This makes it suitable for real-time applications that require instant responses.
How does SonnyLabs help with EU AI Act compliance?
It provides automated compliance tools to determine risk levels and fix gaps quickly. Additionally, the EU AI Act Academy offers intensive training programs to help organizations master regulatory requirements.
Pricing Plans
Free
Free Plan• Real-time threat detection
• Prompt injection protection
• Secure AI agents and chatbots
• Audit or Block modes
• PII leakage detection
• Access to REST API
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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