Sawmills raises $10M in Seed funding to tackle skyrocketing observability costs
New AI-powered platform helps enterprises optimize telemetry data management, enhancing monitoring and reducing costly inefficiencies.
Sawmills, which has developed a telemetry data management platform, has raised $10 million in a Seed round. The round was led by Team8, with participation from Mayfield and Alumni Ventures.
Telemetry is a technology that enables remote measurement and automatic reporting of information. Founded by CEO Ronit Belson, along with Amir Jakoby and Erez Rusovsky—former executives at companies such as New Relic, Tricentis, and CloudBees—Sawmills' AI-powered platform allows enterprises to manage the data flowing from engineering teams to their observability tools, identifying opportunities for cost reduction while enhancing critical monitoring capabilities.
As modern software architectures grow more complex, observability has become critical for maintaining reliable systems - but organizations face dual challenges of unsustainable costs and data quality issues. The median company now spends nearly $2M annually on observability, and the majority of companies report experiencing unexpected cost spikes on a monthly basis. The scale of the problem was highlighted when a financial services firm was famously hit with a staggering $65M observability bill from Datadog.
"Engineering teams are grappling with both cost and quality challenges in their observability data," said Ronit Belson, CEO of Sawmills. "Missing data points, inconsistent formats, and duplicate data drive up costs and make root cause analysis unreliable and time-consuming. Observability has become the second largest expense after cloud costs for most companies. Engineering teams need intelligent telemetry data management that not only improves data quality but also prevents costly mistakes before they happen."
Sawmills enables companies to optimize their observability practices through intelligent data management. The platform uses AI models to analyze telemetry data as it streams through the system, automatically identifying opportunities to reduce spending, improve data quality, and prevent observability system outages.
