ecos is an open FinOps data stack with a CLI and MCP server that turns raw cloud data into actionable insights.

Privacy-first multi-cloud analyzer for AWS and GCP. 200+ scanners covering cost, security posture, IAM, network reachability, CIS compliance, and Well-Architected reviews — with built-in AI chat. Local-only Electron desktop app.

Cut cloud bills, allocate costs, plan commitments, detect anomalies, forecast spend, find waste — AWS/Azure/GCP. FinOps agent skills installable via skills.sh.

Self-hosted Data Observability & FinOps starter kit. Automate pipeline audits, track data freshness/quality, and monitor cloud costs with zero vendor lock-in. Powered by Docker Compose, dbt, Airflow, and Grafana.

OptiOra: OCI-hosted multi-cloud FinOps control plane for live cost telemetry, deterministic optimization, rightsizing, inventory, and OCI GenAI/RAG advisory.

Read-only AWS cost optimization and FinOps audit CLI (Python/boto3). Finds idle EC2/EBS/RDS, orphaned snapshots, unused Elastic IPs and Savings Plan gaps. Prioritized savings report, safe for production.

Menubar app that tracks AI agent quotas, API balances, cloud spend, and subscriptions.

LLM agent for multi-cloud (Azure/GCP) cost triage — natural-language queries, tool-calling, eval harness (Claude/DeepSeek/Ollama)

Baseline daily database spend, detect the spikes that matter, and route an actionable alert naming the offending queries and tables. Runs as a CLI, cron job or GitHub Action.

Attribute cloud database spend to the teams, apps and features that caused it — joins pg_stat_statements deltas with billing exports to produce a defensible chargeback report.

Autonomous FinOps agent engine that detects cloud resource waste (zombie servers) and dynamically routes LLM traffic to optimize cost and performance. Built as a premium glassmorphic dashboard.

S3 cost optimizer — analyzes bucket access patterns, estimates savings from Intelligent-Tiering, Glacier, and Deep Archive policies, and generates automated lifecycle configuration recommendations. Saved $18K/month across 200+ buckets.

GitOps-driven FinOps cost governance on Kubernetes — cost allocation labels, resource quotas, namespace budget limits, and LimitRange policies enforced via GitOps pipeline.

AI/ML cost intelligence engine — ingests cloud cost data, detects GPU spend anomalies, calculates inference efficiency scores, and exports structured financial reports. Built for FinOps teams managing AI workloads at scale.

Harness Cloud Cost Management (CCM) provides intelligent cloud cost optimization with AI-driven recommendations, customizable cost perspectives, budgets, anomaly detection, and chargeback / showback through cost categories.

North.Cloud delivers real-time savings, automated FinOps, and dynamic optimization across AWS and GCP. The platform's public API enables programmatic ingestion and retrieval of cost unit data so teams can integrate unit economics, allocation, and chargeback reporting into their own systems.

FinOps consulting case study for optimizing AWS spend in a fintech multi-account architecture using rightsizing, storage lifecycle policies, and governance controls.

Turn per-team database cost attribution data into a self-contained monthly chargeback report — inline SVG charts, anomaly callouts and budget tracking, no JS required.

Reproducible benchmark comparing CloudHealth vs AWS Cost Anomaly Detection vs Azure Cost Management — measures anomaly detection accuracy, data latency, and metric coverage across providers. Used to justify tooling decisions in multi-cloud environments.

Multi-cloud cost normalization engine — reads AWS, Azure, and GCP billing exports, normalizes under a unified schema (Account, Provider, Service, Date, Cost, Region, Tags), and generates consolidated datasets for dashboards and chargeback.