Transform raw logs into structured knowledge with AI-powered analysis and natural language understanding.
Ask questions like "show me payment failures in the last hour" instead of writing complex regex patterns. Get instant, relevant results.
Receive automated daily digests highlighting key events, anomalies, and trends across all your services—delivered to Slack or email.
Automatically generate comprehensive incident timelines with relevant log entries, correlated events, and root cause analysis.
ML models learn your normal log patterns and alert you when something unusual happens—before it becomes a critical issue.
Automatically suppress noisy logs and highlight what matters. Focus on actionable signals, not endless scrolling.
Connect logs across microservices using trace IDs and request context to see the full story of a transaction.
Automatically parse unstructured logs into queryable fields like user IDs, error codes, and latencies without manual regex.
Replay log streams from any point in time to debug historical issues or validate fixes against past data.
Compare log patterns before and after deployments to quickly identify regressions or performance changes.
Seamlessly integrates with your existing logging infrastructure and tools.
Fluentd, Logstash, Filebeat, Vector, Fluent Bit
AWS CloudWatch, GCP Logging, Azure Monitor, Datadog
Elasticsearch, Splunk, Loki, OpenSearch
K8s Events, Pod Logs, Helm, Kustomize, Operators
Slack, Microsoft Teams, Discord, PagerDuty
Prometheus, Grafana, New Relic, Honeycomb
PostgreSQL, MySQL, MongoDB, Redis, Cassandra
Python, Java, Go, Node.js, .NET, Ruby
Jira, Linear, GitHub Issues, ServiceNow
See how teams are saving hours daily by letting AI read their logs.
96% Faster Debugging
Problem: Engineers spent hours grepping through millions of log lines to debug customer issues. Solution: Natural language search and AI summaries reduced investigation time from 4 hours to 10 minutes.
"I just ask 'what happened to user 12345's checkout?' and get a complete timeline instantly."
— Senior Backend Engineer
Proactive Detection
Problem: Payment gateway issues went unnoticed until customers complained. Solution: Anomaly detection flagged a 3x spike in timeout errors 15 minutes before it would have affected peak traffic.
"The AI caught a pattern we would have missed. Saved us from a potential $200K revenue loss."
— Head of Platform
Audit Ready
Problem: Compliance audits required manually searching logs for specific transactions. Solution: Natural language queries like "show all failed ACH transfers in Q4" made audits trivial.
"What used to take 2 weeks of manual work now takes 30 minutes."
— Compliance Officer
Team Alignment
Problem: Engineering leads had no visibility into daily system health. Solution: Automated daily summaries in Slack showing key metrics, anomalies, and trends across 50+ microservices.
"Our standup meetings are now 10 minutes instead of an hour. Everyone already knows what happened."
— Engineering Manager
Stop drowning in log files. Let AI read, understand, and summarize millions of logs so you can focus on solving problems, not searching for them.