Starseer Platform

Starseer is a platform that secures AI models and agents across three control points: pre-deployment scanning, runtime monitoring, and gateway enforcement. Before a model runs, the platform fingerprints its weights, activations, and architecture against an approved baseline, and uses activation analysis and circuit tracing to detect backdoors or triggers not present in standard test sets. Each scan produces an attested, audit-ready provenance record and can be integrated into a CI/CD pipeline as a gate so unverified models do not reach production. While a model or agent runs, Starseer monitors activations and the decision-to-action chain in real time rather than inferring behavior from outputs alone. Detections are written as YARA-X rules mapped to MITRE ATLAS, and can throttle or isolate a session within milliseconds. Findings feed back into the detection engine and are forwarded to SIEM and SOAR tools, with prompt lineage and traces assembled for analysts. At the gateway, every prompt is classified for intent, complexity, and domain prior to inference, with the platform reporting roughly 38ms added latency compared to 106-570ms for dedicated guard models. Injection, jailbreak, and exfiltration attempts are blocked at this stage. Requests are routed to different sized models based on the complexity the task actually requires, which the vendor states can reduce spend while retaining most frontier-level output quality. The platform deploys via SaaS, on-prem Kubernetes, or fully air-gapped environments, works without application code changes, and supports frontier, open-weight, fine-tuned, and self-hosted models. It aligns evidence output to frameworks including MITRE ATLAS, NIST AI RMF, ISO 42001, and the EU AI Act.