Measure and analyze your language model's behavior from the outside, no weights required.
PSA — Posture Sequence Analysis
Measure and analyze your language model's behavior from the outside, no weights required.
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What it does
PSA, from Silicon Psyche Labs, offers black-box behavioral analysis for language models. It provides deterministic metrics, posture analysis, and multi-agent risk detection without needing access to model weights. Users send text via API or web app, then analyze real-time posture classifiers and agentic graph analysis to detect regime shifts, anomalies, and behavioral drift. The platform integrates subsystems like C0-C4 Classifiers, Silicon Chaos for stress-testing, and SIGTRACK for privacy-compliant incident archiving, all tracing to the Cybersecurity Psychology Framework.
Who it helps
MLOps teams, AI product developers, and security professionals deploying large language models who need to understand and ensure their models' behavior, especially without internal access.
Why it's interesting
PSA addresses the critical and growing need for black-box LLM monitoring and safety, a significant pain point for enterprises. Its unique approach, leveraging a theoretical framework and offering deterministic metrics, provides a robust solution for detecting subtle behavioral shifts and risks. The ability to analyze models without weight access opens up broad applicability and strengthens its market wedge in the rapidly evolving AI landscape.
Card stats
AI-assisted scores estimated from public website information only.
FounderDeck estimate
Medium confidenceFounderDeck estimates PSA at $750,000 due to its highly relevant and critical solution for LLM monitoring and safety in the rapidly expanding AI market. The product demonstrates strong clarity, a detailed feature set, and a robust theoretical foundation, indicating significant development and a clear value proposition for enterprises. While explicit traction or pricing details are not provided, the sophisticated offering and clear market need support a strong early-stage valuation for a B2B SaaS in this space.
Valuation date: 2026-06-05. Estimate generated from public signals.
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