Our mission is to develop an agentic telemetry management platform that enables businesses to fully harness their telemetry data's potential, at petabyte scale and a fraction of the cost.

Sawmills uses AI to analyze your logs and metrics in real time, identifying data that drives up cost without adding value. That includes verbose logging, duplicate entries, and metrics with unused labels. The platform surfaces suggestions for reduction and lets you apply fixes with one click. DevOps and SRE teams can set rules that automatically drop or sample low-value data upstream, before it’s sent to observability platforms like Datadog, Splunk, or New Relic, so you’re not paying for ingestion you don’t need. Best practices for reducing telemetry costs start with this kind of pre-ingestion filtering.

Building and maintaining custom pipelines takes dedicated engineering time. Sawmills gives teams a no-code interface to configure routing, filtering, and aggregation without writing or maintaining custom code. It’s one of the best alternatives for companies that want pipeline-level control but don’t have the resources to build it from scratch. Compared to other pipeline tools and platforms, Sawmills is easy to deploy, requires minimal configuration, works across multiple destinations, and handles the complexity of multi-collector environments out of the box.

The Telemetry Explorer gives you structured views of all your telemetry data, broken down by service, source, and type (logs and metrics). From there, the AI surfaces cost and quality insights, like which services are sending the most data, where you have high-cardinality spikes, or which log patterns are repeating. You can take corrective actions directly in context instead of switching between multiple tools and dashboards. The goal is to simplify triage for teams managing telemetry across services.

Yes. Sawmills includes telemetry resource allocation and source attribution, so you can see exactly which teams and services are producing what data and how much it costs. This makes it possible to set budgets per team, track spending over time, and hold departments accountable for their telemetry footprint. For large SaaS and enterprise companies, this kind of visibility is one of the best strategies for bringing observability costs under control without top-down mandates.

Most standard pipeline tools focus on routing and transformation. Sawmills goes further by using AI to detect optimization opportunities that manual rules miss, like redundant log patterns and underused metric labels that could be sampled without losing diagnostic value. The platform recommends specific actions (drop, sample, aggregate, route) and shows the projected cost reduction for each one, so teams can make informed decisions rather than guessing where to cut.