A: Grepr works with Datadog, Splunk, New Relic, Sumo Logic, Grafana Cloud, and any OpenTelemetry-compatible platform. You query the Grepr data lake using the same query language you already know: SPL for Splunk, Lucene for Datadog and New Relic. No new query language to learn.
A: Grepr accepts data from Fluent Bit, Fluentd, Logstash, the Datadog Agent, Splunk Universal Forwarder, and any shipper that supports standard output protocols. Setup is a configuration change, not a reinstall.
A: Yes. Grepr sits between your agents and your platform backend. Your existing dashboards, alerts, and workflows stay exactly where they are. Grepr reduces what reaches your platform backend by 90% or more, which cuts the bill without touching anything your engineers depend on daily.
A: Yes. Grepr is SOC 2 Type II certified. You can review the full trust report at trust.grepr.ai.
A: Raw log data is stored in your own S3 bucket, not Grepr's infrastructure. Grepr writes using Apache Iceberg and Apache Parquet, open formats you control. You set the retention period, tiering rules, and access permissions independently of Grepr.
A: Grepr processes your data in transit to apply ML-based aggregation and routing. Raw data lands in your S3 bucket, which you own and control. Grepr does not retain copies of your raw data on its own infrastructure.
A: Yes. Grepr supports SAML-based SSO, including Okta and most major SSO providers, to simplify user management and meet enterprise compliance requirements.
A: Most teams have their first pipeline running in about 20 minutes. You create a pipeline in the Grepr dashboard and reconfigure your existing agents to send data to Grepr instead of directly to your observability platform. No new agents, no instrumentation changes, no code deploys.
A: No. Grepr works at the shipper layer, not the application layer. Your application continues logging exactly as it does today.
A: Yes. Grepr's Live View feature clones your production pipeline so you can validate configuration changes against real data streams without any deployment risk or impact on your live environment.
A: Grepr is primarily offered as a SaaS platform, but can also be deployed on your own infrastructure, whether physical or virtual, for teams with strict data residency or network requirements.
A: Grepr is built on autoscaling serverless infrastructure designed for high availability. In the event of an interruption, you can reconfigure your agents to send directly to your observability platform temporarily, using the same configuration change you made during setup.
A: Grepr's ML continuously learns your environment and builds a catalog of dashboards and alerts it will never touch. You also have direct controls to mark specific log patterns, sources, or severity levels as pass-through. Everything is retained in the data lake if you need to query it.
A: Grepr offers documentation at docs.grepr.ai and direct support for all customers. Enterprise customers receive dedicated support. Contact the team at grepr.ai/contact for specifics.
A: Pricing is based on three components: compute-unit usage (how much processing work Grepr does on your behalf), data ingestion volume (SaaS only), and data lake query volume (SaaS only). There is no flat per-seat or per-host fee.
A: Most customers see 90% or more reduction in data volume sent to their observability platform. FOSSA reduced log volume by 95%. Goldsky saw a 96% reduction in Datadog logging costs. Results depend on how noisy your current log stream is.
A: Yes. You can get started free at app.grepr.ai/signup. Most teams see results within the first 20 minutes of setup.
A: Grepr charges based on how much data you send for processing and how much compute work it does on your behalf, not on how much you save. The more volume you send through Grepr, the more you save on your downstream platform costs relative to what you pay Grepr.
