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Autonomous cloud discount management with ML

ProsperOps uses machine learning to continuously optimize cloud commitment coverage including Savings Plans and Reserved Instances, achieving Effective Savings Rates of 40% or more on AWS, GCP, and Azure. It provides autonomous discount management with a performance-based pricing model where ProsperOps shares a percentage of the savings generated, aligning costs with actual value delivered.

Autonomous Kubernetes cost optimization

CAST AI automates Kubernetes cost optimization by analyzing workloads in real time and taking direct action on clusters, including right-sizing pods, selecting optimal instance types, and leveraging spot instances automatically. The platform achieves up to 60% cost reduction without human intervention, offering a free cluster audit that identifies savings opportunities before any commitment.

Open-source Kubernetes cost monitoring (CNCF)

OpenCost is a CNCF-certified open-source tool for real-time Kubernetes cost monitoring that maps cloud spend directly to namespaces, deployments, pods, and labels. It provides granular cost allocation across teams and projects without vendor lock-in, supporting AWS, GCP, Azure, and on-premises clusters as the industry standard for open-source FinOps visibility in cloud-native environments.

Kubernetes operator for serving AI inference workloads

KubeAI is an Apache-2.0 Kubernetes operator for deploying and scaling AI inference workloads, including LLMs, embeddings, reranking, and speech-to-text. It gives platform teams OpenAI-compatible endpoints, model proxy/controller primitives, model caching, scale-from-zero behavior, and cluster-native resource management for self-hosted inference on Kubernetes.

Sandboxes for coding agents — Linux VMs, Git, and deploys in one box

Freestyle is YC-backed sandbox infrastructure built for AI coding agents, shipping secure Linux VMs with nested virtualization, Git servers, and one-click web deploys. It lets agents run real workloads, branch repos, and deploy apps under short-lived identities while billing only for active compute. Used in production by vly.ai, Rork, and Vibeflow.

Open-source toolkit for building AI SRE incident response agents

OpenSRE is Tracer Cloud’s open-source public-alpha Python toolkit for building AI SRE agents that investigate and respond to production incidents. It ships 60+ tools across observability, databases, incident management, communications, deployment and protocol integrations, plus simulation/evaluation workflows for benchmarking agent accuracy before live pager use.

See where your AI coding tokens actually go

Open-source TUI dashboard and CLI that shows where your AI coding tokens actually go, broken down by task type, tool, model, MCP server, and project. CodeBurn reads local session data directly from Claude Code, Codex, Cursor, OpenCode, Pi, and GitHub Copilot — no wrapper, proxy, or API keys — and layers on one-shot success rates so you can see whether the AI nails work first try or burns budget on edit/test/fix retries. Ships with a macOS menu bar widget and CSV/JSON export.

Autonomous coding agents that ship while you sleep

Twill is an autonomous coding agent platform that implements features, fixes bugs, and ships pull requests without manual intervention. Uses structured workflow of research, planning, human review, implementation in isolated sandbox, AI code review, then merge. Supports custom agent configurations with multiple LLM providers, isolated dev environments for verification, and integrations with GitHub, Linear, Sentry, Notion, and cloud platforms for end-to-end engineering automation.

ML inference platform for production AI models

Baseten is the inference platform for deploying AI models at scale with dedicated and pre-optimized model APIs and performance-optimized infrastructure. Specializes in image generation, transcription, text-to-speech, LLM serving, embeddings, and compound AI workloads. Delivers 75% latency reduction with 415ms cold starts and 3000+ concurrent scaling. Available as managed cloud or self-hosted, trusted by Cursor, Notion, Descript, and Sourcegraph for production inference.