Stop Reading Logs. Start Understanding Them.

Our AI converts your plain English questions into optimized queries across your log data. It understands context, synonyms, and intent—no need to memorize field names or syntax.

Yes! We integrate with Elasticsearch, Splunk, CloudWatch, Datadog, Loki, and more. You keep your existing infrastructure—we add the intelligence layer on top.

Our AI analyzes all logs from the past 24 hours, identifies key events, anomalies, and trends, then generates a human-readable summary delivered to Slack, email, or your dashboard.

We automatically detect and redact PII (emails, credit cards, SSNs) before processing. You can also define custom scrubbing rules and run the agent on-premise for full data control.

The ML model trains on your historical log patterns (volume, error rates, latency) for 7 days, then continuously adapts. It learns your deployment schedules and traffic patterns to reduce false positives.

Yes, you can define templates for incident reports including which fields to include, formatting preferences, and where to send them (Jira, Slack, email, etc.).

We retain summaries and insights for 90 days by default. Raw logs stay in your existing storage (Elasticsearch, S3, etc.)—we don't duplicate them.

Absolutely. We can aggregate logs from AWS, GCP, Azure, and on-premise systems into a unified view, making cross-cloud debugging seamless.

We charge based on log volume processed (GB/month), not per user. There's a free tier for up to 10GB/month, perfect for small teams and side projects.

Splunk and Datadog are powerful but require manual query building. We add an AI layer that understands natural language, generates summaries, and proactively surfaces insights—no SPL or regex required.