Tame the chaos of Production environments
Grepr separates signal from noise and enables you to build proactive, autonomous agents that catch what nobody thought to look for.
Detect anomalies, remediate incidents, and optimize telemetry.
Production changes faster than your rules keep up
AI multiplies how fast code ships and how fast attacks evolve. Alerts, detections, and parsers only cover what someone already predicted. Meanwhile, observability bills force you to drop data, which creates blind spots where new problems hide.
Broken quietly
A field renamed upstream silently breaks dashboards, alerts, and SIEM detections.
Found too narrowly
Threats hide in logs that no detection covers.
Found too late
Reliability issues surface from lagging SLOs, after customers already feel them.
Noise costs you twice
Teams pay to index noise, then drop data to control the bill and suffer the blind spots.
What no alert sees
Every rule encodes a lesson someone already learned. These are the problems nobody wrote a rule for.
Examples:
Batteries included:
A complete platform for
AI-powered ops.
Grepr sits between your telemetry sources and the tools you already use. It separates signal from noise in real time, notices what’s new, and gives your agents what they need to act on it.
Signal processor.
The unique engine that powers the Grepr platform.
Processes raw telemetry at scale, extracts signals and powers agents, shapes and optimizes data, and runs complex rules using streaming SQL. Sends compressed signal to your existing tools to minimize cost.
Grepr AI.
A harness for building proactive operational agents.
Build agents that investigate new data patterns, fix problems at the source, and hand off to the agents and systems you already use, across performance, reliability, and security.
Data Lake.
Collect everything.
A low-cost observability data lake that eliminates compromises between cost and visibility. Grepr’s data lake is 50% cheaper than other solutions. Keep control of your data using your own object storage.
Build agents that run your operations.
You already use coding agents to build software. Use Grepr to build agents that run it in production.
Every environment fails in its own way. Describe the job in plain language, connect your tools, and subscribe the agent to a pipeline. It starts finding issues and working on them immediately.
How it works
Connect the MCP servers your agents should reach.
Create an agent and tell it what to do in plain language: how to investigate signals and how you want to be notified if it finds anything worth flagging.
The agent starts receiving new signals as they appear. Default signals differ by data type, or you can create your own using streaming SQL.
See what agents are working on, and coordinate between humans, Grepr agents, and other agents using MCP.
Connect the agents you already run to the Issues board and data lake through MCP.
Instead of waiting for an alert
Agents start the moment something changes.
Instead of hand-tuned filters
Get dynamic noise reduction that adapts as your data changes.
Instead of sampling or dropping data
Keep every raw event for investigations and compliance.
Instead of replacing tools
Keep your existing tools, dashboards, and alerts.
Fully running in 30 minutes
A single configuration change points your collectors to Grepr. No new infrastructure to deploy.
Create a new agent with your prompt, and tell it what you want it to do.
Compressed signal and summaries go to your observability and security platforms. Send to multiple tools at once.
Grepr passes through the data that powers them, with no impact on existing operations.
Find problems before your customers
“Our developers are happy, because we didn't change how they operate, which is exactly what I wanted. And now our costs have dropped.”
How a Medical Technology Company Reduced Log Volume by 94% While Maintaining Reliability
“I've been through a lot of vendor evaluations, and this was the smoothest POC we've experienced.”
How a Global Retailer Stopped Paying to Index Noise
“We were skeptical that something could reduce our log volume that aggressively without us feeling it somewhere. The fact that our developers haven't noticed a change in how they work is the result we were hoping for.”
How CustomInk Cut Their CloudWatch Bill by 85% Without Impacting Dev or Ops
“After seeing what Grepr did to reduce our logs noise, extending it to traces was an easy call. We were seeing the same pattern: a lot of volume, most of it not particularly useful, and a Datadog billing model that scaled with every new host we spun up.”
How FOSSA Reduced Distributed Trace Volume by 90%
“Engineers didn't change how they work at all. Dashboards and alerts still worked as expected. We just stopped paying for 90% of our log volume that was never doing anything for us.”
9 Days from Kickoff to Production: How Envoy Cut Log Volume by 90%
"Grepr helped us automate what to keep and what to skip, so we’re not paying to store or index noise. It lets us find the needle in the haystack without paying for the haystack!"
How Jitsu Cut Logging Costs by 90% While Managing Millions of Shipments Generating 400 Logs Each
"Since we deployed Grepr, we’re seeing a 95% reduction in log volume and didn’t have to change a thing in our app. I'd recommend Grepr to any team that's experiencing rising costs from an expensive logging platform!"
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Case Study: How FOSSA Reduced Their Logs by 95% Without Burdening Their Engineers
“Our developers are happy, because we didn't change how they operate, which is exactly what I wanted. And now our costs have dropped.”
“I've been through a lot of vendor evaluations, and this was the smoothest POC we've experienced.”
“We were skeptical that something could reduce our log volume that aggressively without us feeling it somewhere. The fact that our developers haven't noticed a change in how they work is the result we were hoping for.”
“After seeing what Grepr did to reduce our logs noise, extending it to traces was an easy call. We were seeing the same pattern: a lot of volume, most of it not particularly useful, and a Datadog billing model that scaled with every new host we spun up.”
“Engineers didn't change how they work at all. Dashboards and alerts still worked as expected. We just stopped paying for 90% of our log volume that was never doing anything for us.”
"Grepr helped us automate what to keep and what to skip, so we’re not paying to store or index noise. It lets us find the needle in the haystack without paying for the haystack!"
"Since we deployed Grepr, we’re seeing a 95% reduction in log volume and didn’t have to change a thing in our app. I'd recommend Grepr to any team that's experiencing rising costs from an expensive logging platform!"
Find out what your telemetry has been trying to tell you
Cut telemetry costs 90%, then put agents to work on problems nobody looked for