CalypsoAI

LLM Red Teaming

Automated adversarial testing of LLMs for jailbreaks, prompt injection, and unsafe outputs.

LLM Guardrails

Runtime input/output filtering for LLMs — PII redaction, toxicity blocking, prompt injection defense, policy enforcement.

LLM Guardrails & Content Filtering

Runtime guardrails that block or redact unsafe prompts and responses in production LLM applications.

Hallucination Detection

Automated scoring of LLM outputs for factual accuracy and groundedness, typically via retrieval-backed verification or reference comparison.

Prompt Management

Versioning, templating, A/B testing, and deployment workflows for LLM prompts treated as production artifacts.

Audit Logging

Tamper-evident logging of governance events (approvals, model changes, policy decisions) required by EU AI Act Article 12 and similar regulations.

LLM Observability

Logging, tracing, and metrics for LLM applications in production — latency, cost, quality, and error rates across traces and users.

LLM Evaluation

Systematic testing of LLM outputs for correctness, relevance, safety, and consistency using automated scorers, rubrics, or human review.

AI Incident Response

Documented workflows for detecting, investigating, and remediating AI-related incidents including bias events, safety failures, and security breaches.