Why we built Cletrics
After a decade watching engineering teams find out about cost spikes the morning after they happen, we built Cletrics to close the visibility gap that every native cloud cost tool inherits — without rebuilding the way your team works.
The problem we kept seeing
The same disaster pattern repeats at every cloud-heavy company we've worked with: a misconfigured autoscaler, a runaway AI training job, a leaked NAT Gateway, or a security breach burns $20,000–$200,000 between Friday night and Monday morning. By the time AWS Cost Explorer (or Azure Cost Management, or GCP Billing) catches up, the cost has already compounded for 18–24 hours.
The reason this keeps happening is structural. Cloud billing data flows through a multi-stage batch ETL pipeline: service-level metering → regional aggregation → cross-region consolidation → pricing apportionment → CUR generation → Cost Explorer ingestion. Each stage adds latency. Total: 8–14 hours typical, up to 36+ hours under load. Every "FinOps platform" you've heard of (Vantage, CloudZero, Apptio, Kubecost) builds on top of this pipeline, so they all inherit the same lag.
That's fine for monthly finance reporting. It's catastrophic for operational alerting. We built Cletrics to bypass the billing pipeline entirely — pulling infrastructure telemetry at 1-minute resolution, joining it against current pricing data in memory, and applying per-workload weighting calibrated against your actual past bills. Real-time cost visibility, accurate to 99%+ of the eventual bill.
Who builds Cletrics
Jeff Symons
Founder · RunAI Pilot
Cloud and FinOps engineer with a decade in production cloud at the intersection of platform engineering and cost optimization. Started Cletrics after watching the same "found out about it Monday" cost incident play out one too many times. Based in Dallas-Fort Worth, Texas.
The architecture, briefly
Cletrics has three layers:
- Telemetry layer. Read-only collectors pull metrics from CloudWatch, Azure Monitor, and Google Cloud Operations at 1-minute resolution. No agents inside customer workloads. Same permission surface as Datadog or any APM tool.
- Calibration Engine. A reconciliation process that compares live telemetry-derived spend against your actual past bills, learns per-workload discount weights (RIs, Savings Plans, EDPs, CUDs), and applies those weights to live data. End result: 99%+ accuracy in real-time without waiting for the official billing pipeline.
- Anomaly + alerting layer. ML-based anomaly detection at 60-second resolution. Slack, PagerDuty, and webhook integration for circuit-breaker workflows. Per-team budget guardrails with hard-stop capability.
For a deeper architectural read, see our post Solving the 30-Day Cloud Billing Black Box.
What we believe
- Cloud cost is a production metric. It belongs in the same dashboards as latency and error rate, not in a quarterly finance report.
- Engineers should own unit economics. Cost-per-customer and cost-per-feature create ownership; total cloud spend creates blame games.
- Real-time accuracy beats forensic precision. 99% accurate in 60 seconds is more operationally useful than 100% accurate in 24 hours.
- FinOps tools should integrate, not replace. We're complementary to your monthly CUR-based reporting, not a substitute. Use both.
Where Cletrics fits in the FinOps Foundation framework
Cletrics is built explicitly to map to the FinOps Foundation's three-phase framework:
- Inform: Real-time multi-cloud dashboards, unit economics queries, cost attribution by team / project / customer / feature.
- Optimize: Anomaly Explorer for orphaned and zombie resource detection, AI/GPU cost tracking, right-sizing recommendations driven by live utilization data.
- Operate: Slack and PagerDuty alerting at 60-second resolution, webhook circuit breakers for runaway workloads, per-team budget guardrails with hard-stop capability.
Customer commitment
Three guarantees we make to every customer:
- Read-only by default. Cletrics never has write access to your cloud accounts. Cost remediation actions are always behind explicit human approval or your own webhook automation.
- Calibration accuracy disclosure. Every account dashboard publishes the live delta between Cletrics-estimated spend and your actual bill. You audit us continuously.
- Data residency control. Hosted today; self-hosted (in-VPC) deployment available for enterprise customers with strict data residency requirements. Email hello@realtimecost.com for the deployment guide.
Get in touch
Questions, demos, partnership inquiries, or just want to argue about CUR latency:
- Email: hello@realtimecost.com · jeff@runaipilot.com
- Schedule a 20-minute walkthrough: Calendly
- LinkedIn: linkedin.com/company/cletrics