See how LogLens transforms natural language into powerful observability insights through our intelligent processing pipeline.
Ask your question in plain English. No need to know KQL, SQL, or any query syntax.
Example Query
"Show me all 500 errors in the checkout service from the last hour where response time exceeded 2 seconds"
Our NLP engine understands intent, context, and your infrastructure topology.
Entity Recognition
checkout-service
Time Range
now-1h to now
Conditions
status:500, latency>2s
Automatically generates optimized queries in your data source's native language.
Generated KQL Query
service:"checkout-service"
AND status:500
AND response_time_ms > 2000
AND @timestamp >= now-1h
| stats count() by endpoint, error_message
| sort -countQuery executes across your connected data sources in parallel with smart caching.
Datadog
✓ 124ms
Elasticsearch
✓ 89ms
Prometheus
✓ 56ms
Custom API
✓ 102ms
AI correlates signals across logs, metrics, and traces to identify the real issue.
Database connection pool exhaustion
→ Detected spike in connection wait time (metrics)
→ Correlated with "connection pool timeout" errors (logs)
→ Traced to recent traffic surge from marketing campaign (traces)
Get explainable visualizations, natural language summaries, and shareable insight cards.
Visual Charts
Plain English Summary
Shareable Cards
LogLens leverages the latest advances in AI, distributed systems, and query optimization.
Fine-tuned models specifically trained on observability queries and incident data.
Multi-tier caching system reduces query latency by up to 90%.
Advanced algorithms detect causal relationships across different signal types.
Read-only access with zero data storage ensures your data never leaves your infrastructure.
Based on production usage across 500+ teams
Average Query Latency
Query Translation Accuracy
Root-Cause Confidence
Faster Incident Resolution
Watch a live demo or try our interactive playground with sample data.