LogParsed.

How we achieve 1,000,000+ RPS.

LogParsed uses a revolutionary FSM-Fallback engine coupled with a deterministic Regex Cache to normalize OCSF logs at wire-speed, drastically outperforming standard LLM-based parsers.

Firehose

1M+ RPS

99% Volume

Regex Cache

0.08ms latency

1% Volume

AI FSM

Self-healing LLM

Sink Router

Snowflake
Splunk
AWS S3

The Hot Path

When a log matches a known vendor format, we extract the variables using a pre-compiled Python Regex AST. This completely bypasses the LLM, parsing events in less than 0.08ms per log. This handles 99% of your traffic.

FSM Fallback

When a log format changes (e.g. AWS updates CloudTrail), the fast path misses. The log is instantly routed to a Pydantic-constrained LLM which extracts the OCSF data AND generates a new regex signature to heal the Fast Path automatically.

Async Sinks

Logs don't just sit in the engine. After parsing, they hit an asynchronous Sink Router which batches and flushes JSON directly to your chosen destination (Snowflake, Splunk, S3, or Kafka) without blocking the ingestion API.