The right plan for every team.

Wrap your pipeline with server-side security scanning before any data is stored. Fluiq checks every prompt and response, so attack patterns are never shipped in the public SDK.

• PII Detection & Redaction: Names, emails, phone numbers, SSNs, and credit cards, detected and redacted before persistence.
• Prompt Injection Blocking: Catches injection patterns, jailbreak attempts, and skeleton key attacks in real time.
• Jailbreak & Semantic Attack Scoring: Semantic similarity scoring against known attack vectors, even when phrasing varies.
• Secret Leak Prevention: Scans LLM outputs for leaked API keys, tokens, and high-entropy credential strings.
• Indirect Injection Detection: Inspects tool outputs and context documents for second-order injection hidden in retrieved content.
• Warn or Block mode: warn (default) flags risks and attaches security metadata to the trace. block intercepts before the LLM call and raises FluiqSecurityError.

fluiq.instrument(api_key="fl_...")
fluiq.secure()  # warn mode flags risks on the trace
fluiq.secure(mode="block")  # block mode

Fluiq analyses your historical traces to find which LLM calls repeat most often and provisions a dedicated Redis cache for your account. Repeated prompts are served instantly, saving both latency and cost.

• Trace-Driven Cache Profiling: The backend mines your trace history to build a cache profile, no manual configuration needed.
• Automatic Cache Population: Real LLM responses are stored automatically on the first call; subsequent matches are served from Redis.
• Cache mode: Full interception: matching prompts never reach the LLM API.
• Observe mode: Records what would have been a cache hit without intercepting: review your savings before opting in.
• Zero code changes: One fluiq.optimize() call after instrument(). The SDK handles connection, profiling, and cache lookup.
• Cache hit dashboard: See hit rates, latency savings, and estimated cost savings in your Fluiq dashboard.

fluiq.instrument(api_key="fl_...")
fluiq.optimize()  # cache mode
fluiq.optimize(mode="observe")  # observe mode