Coreplane Labs
Coreplane Labs builds Polylane, AI agents intended to make software self-operating: they read code, watch infrastructure and telemetry, investigate production issues, and write or open fixes. Its stated mission is that nobody should be on-call.
At a Glance
- Software engineering and platform teams
- DevOps and SRE teams
- Startups and technology companies operating production cloud workloads
- Teams using AI coding agents that need production context
- +1 more
AI Tools by Coreplane Labs
(1)
Polylane
AI Agents for Infrastructure Fixes
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Latest News
We swapped our LLMs for Jev. It's 39% cheaper.
How we prevent slop from hitting prod: production-aware review and investigation workflow.
Sub-agents are just wrong: Polylane's single-agent investigation architecture.
Build log: one agent from finding an issue to opening a pull request; Grafana Cloud and Logfire added as observability integrations.
Products & Services
An AI-agent platform for production operations. It connects cloud resources, code repositories and telemetry into a live context graph; detects issues, triages alerts, investigates root causes with evidence, evaluates pull-request impact, instruments blind spots, and can produce verified autofix pull requests. It also provides a Slack agent, CLI, platform MCP server and API access.
Market Position
Coreplane positions Polylane as a production-operating agent layer rather than a conventional dashboard or telemetry store: it connects code, cloud and observability data, determines whether an issue is real, investigates the cause, evaluates changes against live infrastructure and can open a verified fix. This differentiates it from traditional observability and incident-management products that primarily collect telemetry, alert or coordinate response; the relevant adjacent tools shown in its integration ecosystem include Datadog, Sentry, PagerDuty and Linear.
Leadership
Founders
Boris Tane
Previously founded Baselime, an observability platform acquired by Cloudflare in 2024, and then led observability at Cloudflare.
Executive Team
Boris Tane
Founder and CEO
Founded Baselime, later acquired by Cloudflare in 2024, and led observability at Cloudflare before founding Coreplane Labs.
Founding Story
Coreplane Labs says it was started because observability tools became good at storing telemetry but poor at answering the operational questions that matter during an incident: what broke, why it broke, and how to fix it. The initial vision was software that detects issues from real signals, investigates using the team's own tools, takes reversible action where allowed, and writes the permanent fix while leaving the team in control of production.
Business Model
Revenue Model
Subscription software with usage-based monthly AI credits. Paid workspaces are billed monthly or annually; Scale and higher plans can enable pay-as-you-go overage, while Enterprise uses volume pricing.
Pricing Tiers
Free forever; 2 team members, up to 2 cloud accounts, unlimited repos and integrations, monthly credits, and 10 PR reviews per month.
10x Free usage; up to 5 cloud accounts; unlimited seats; 500 PR reviews per month.
40x Free usage; unlimited cloud accounts and seats; 2,000 PR reviews per month; shared memories and custom instructions.
100x Free usage; unlimited cloud accounts and seats; 5,000 PR reviews per month.
160x Free usage; unlimited cloud accounts and seats; 8,000 PR reviews per month; pay-as-you-go overage.
400x Free usage; unlimited cloud accounts and seats; 20,000 PR reviews per month; pay-as-you-go overage.
1,000x Free usage; unlimited cloud accounts and seats; 50,000 PR reviews per month; pay-as-you-go overage.
Unlimited usage allowances; bring your own LLM provider API key, AI gateway or cloud; dedicated support.
Target Markets
- Software engineering and platform teams
- DevOps and SRE teams
- Startups and technology companies operating production cloud workloads
- Teams using AI coding agents that need production context
- Organizations running AWS, Cloudflare, Vercel, Kubernetes and other supported cloud platforms
- Incident response and root-cause investigation
- Proactive production issue detection, including failures that did not generate an alert
- Production-impact analysis before code merges
- DevOps and cloud operations across a distributed stack
- Ticket and bug resolution through investigation and a proposed fix
- Giving coding agents production context
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