Fluent Bit, Logstash, Vector, OpenTelemetry Collector, or direct HTTP. Parseable accepts logs from every shipper your stack already uses, with no re-instrumentation required.
Query logs with the SQL your team already knows, or ask a question in plain English and let Parseable generate and run the query. Dashboards and alerts use the same interface.
Spot patterns before they spread. Use AI summaries to understand log patterns quickly and forecasting to identify unusual trends earlier. Parseable helps teams move from reactive searching to proactive log monitoring.
Why Parseable
Parseable gives teams one place to ingest, search, query, visualize, and alert on logs without stitching together a separate logging stack. Logs can be investigated with SQL, plain-English queries, AI summaries, dashboards, and alerts.
Every log stream lands in columnar Parquet on S3, GCS, or Azure Blob. Each field is its own column, so querying severity never reads message or any other column you did not ask for.
Ask a question in plain English and Parseable generates and executes the SQL. Switch to raw SQL when you need full control.
Jump from a log line to the trace that produced it, or pivot to metrics for the same time window. Parseable correlates signals across logs, metrics, and traces without a separate tool.
Parseable AI groups related log lines into clusters, surfaces the root-cause pattern, and writes a plain-English summary so your team spends time on the fix, not the search.
AI summary
db-postgres connection pool exhausted. 312 ERROR logs in 90s, all from billing-worker. Upstream cascade from api-gateway timeout at 10:41:58.
Set alerts on error rate, log volume, missing heartbeats, or any SQL condition. Route to Slack, PagerDuty, email, or webhooks without adding a separate alerting layer.
Use Cases
Monitor applications, databases, infrastructure, network, and cloud providers from a single platform. Parseable's columnar storage keeps high cardinality telemetry manageable without forcing you to drop labels or cap retention.
Monitor applications, databases, infrastructure, network, and cloud providers from a single platform. Parseable's columnar storage keeps high cardinality telemetry manageable without forcing you to drop labels or cap retention.
Leverage telemetry data from MCPs, LLMs, and Agents to build end-to-end visibility with confidence. Track token usage, latency per model, and cost across inference calls.
Total sessions
1,246
−12%
Total tokens
18.2M
+23%
Latency P95
5.32s
−7%
Error rate
2.4%
−17%
My order #88821 hasn't arrived and I'd like a refund...
My package was supposed to arrive yesterday, can you...
I received the wrong item and I would like to exchange...
I want to delete my account and all associated data...
I just wanted to say how great the support was during...
Can you confirm that my payment of $142.50 was processed...
I'd like to upgrade my plan to Pro but the button isn't...
Understand user behavior, feature adoption, and performance to optimize the user experience. Correlate product events with infrastructure telemetry for a complete picture.
Capture and analyze user activity, system events, and security logs to ensure compliance and security. Columnar storage keeps audit queries fast even at billion-event scale.
2026-04-29T09:23:59.847
2026-04-29T09:24:01.203
Also from Parseable
Handle high-cardinality logs, metrics, and traces at a fraction of the cost with columnar storage.
Unify Kafka metrics, logs, and traces to catch lag, replication issues, and broker failures earlier.
See why Parseable is purpose-built for observability where ClickHouse leaves teams to build their own stack.
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