Blindsight provides runtime security for AI applications by detecting and blocking a wide range of hidden threats, including prompt injections, jailbreak strings, shadow AI usage, back‑doors, and data poisoning. The platform continuously monitors unsanctioned AI tools and model behavior in production, offering free discovery of unauthorized AI deployments and real‑time alerts to prevent data leakage and bias infiltration.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises deploying AI models lack visibility into runtime threats such as prompt injections, jailbreak strings, hidden back‑doors, poisoned data, and the use of unsanctioned AI tools, leaving models vulnerable to sophisticated attacks that traditional security solutions do not detect.
Solution
Blindsight provides a runtime security platform that continuously monitors deployed AI models for a wide range of attacks, from obvious prompt injections to covert back‑doors and data poisoning. The system detects shadow AI usage by identifying unsanctioned tools operating within an organization, even when they bypass existing security stacks. Detected threats generate real‑time alerts, enabling security and engineering teams to intervene before damage occurs. By exposing hidden vulnerabilities and providing actionable insights, Blindsight helps organizations deploy AI with greater confidence and speed.
Target Audience
Primary customers are enterprise AI teams, security operations centers, and compliance officers responsible for deploying and protecting large language models and other AI systems in regulated environments.
Features
- Continuous monitoring of AI model behavior to identify prompt injections, jailbreak strings, and adversarial inputs
- Detection of hidden back‑doors and trigger keys embedded in model weights
- Identification of shadow AI tools and unsanctioned copilots used by employees
- Scanning for mislabelled, low‑quality, or poisoned training data that can bias model outputs
- Runtime analysis of Retrieval‑Augmented Generation (RAG) pipelines to catch malicious content in retrieved documents
- Monitoring for demographic shortcut learning and other bias‑related issues
- Real‑time alerting and reporting dashboard for security and DevOps teams