FILTAR provides a real‑time security layer for enterprise LLM deployments, intercepting requests and responses to detect prompt‑injection attacks and redact sensitive data. Its configurable policy engine enforces regulatory rules such as GDPR, PCI‑DSS, and HIPAA, while lightweight SDKs and API gateways enable low‑latency integration with existing model‑serving stacks. All events are logged to a tamper‑evident audit trail and presented in a centralized dashboard with alerts, risk scores, and compliance metrics.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises that deploy large language models in regulated industries risk prompt injection attacks, inadvertent data leakage, and non‑compliant AI behavior, which can lead to regulatory penalties and loss of customer trust.
Solution
FILTAR delivers a real‑time security layer that intercepts LLM requests and responses, applying a configurable policy engine to block malicious prompts and strip sensitive information before it leaves the system. The platform integrates with existing model‑serving pipelines via lightweight SDKs and API gateways, ensuring minimal latency while providing continuous monitoring. Built‑in agent‑to‑agent authentication secures internal AI services, and all events are logged to a tamper‑evident audit trail for compliance reporting. Administrators can define regulatory rule sets (e.g., GDPR, PCI‑DSS) that the system enforces automatically, reducing the operational burden of manual review. A centralized dashboard surfaces alerts, risk scores, and compliance metrics, enabling security teams to respond quickly to emerging threats.
Target Audience
Primary customers are banks, insurers, healthcare providers, and telecom operators that run LLM‑driven applications such as customer support, risk assessment, and decision automation in regulated environments.
Features
- Real‑time prompt‑injection detection using pattern matching and LLM‑based guardrails with sub‑10 ms overhead
- Output sanitization and token‑level redaction to prevent data leakage across model responses
- Configurable policy engine supporting industry‑specific regulations (GDPR, PCI‑DSS, HIPAA, etc.)
- Mutual TLS and token‑based agent‑to‑agent authentication for secure intra‑AI communication
- SDKs and API gateways for seamless integration with popular serving stacks (LangChain, OpenAI, Azure, on‑prem)
- Centralized console with live alerts, risk scoring, and exportable audit logs for regulator‑ready reporting
- Multi‑cloud and on‑prem deployment options with containerized microservices for scalability
- Role‑based access control and encrypted storage to meet enterprise security standards