# cost-reduction

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.

CLI token usage tracker for AI coding agents

Tokscale is a CLI tool that tracks token usage and costs across AI coding agents including Claude Code, Codex, OpenCode, Gemini CLI, Cursor, and more. Built with a native Rust core for high-performance processing, it provides detailed breakdowns of input, output, cache, and reasoning tokens with real-time pricing calculations via LiteLLM data. Features include interactive 2D/3D contribution graphs, web visualization dashboards, global leaderboards, and JSON export for cost analysis.

Smart LLM router that cuts inference costs up to 70%

Manifest is an open-source smart model router that intelligently routes LLM requests to the cheapest capable model, reducing inference costs by up to 70% without sacrificing output quality. It uses a 23-dimension scoring algorithm to evaluate 300+ models across providers including OpenAI, Anthropic, Google, and DeepSeek, with automatic fallbacks and budget controls. Manifest can be deployed as a cloud service, local plugin, or self-hosted Docker container with transparent routing logic.

FOCUS-native multi-cloud cost management and FinOps platform

Holori is a multi-cloud cost management platform built on the FOCUS billing data standard. It provides unified cost visibility across AWS, Azure, GCP, and other cloud providers with automated tagging, budget alerts, and optimization recommendations. Features interactive infrastructure diagrams that link architecture visualization directly to cost data for contextual spending analysis.

AI-powered autonomous cloud cost optimization for AWS

Zesty uses AI to automatically optimize AWS cloud costs by analyzing usage patterns and making real-time resource adjustments. It manages Reserved Instance and Savings Plan portfolios autonomously, right-sizes EC2 instances based on actual utilization, and optimizes EBS volumes and storage costs. Claims average 51% savings on AWS compute spend with no engineering effort required.

Kubernetes cost monitoring and optimization platform

Kubecost provides real-time cost monitoring and optimization for Kubernetes clusters. It allocates infrastructure costs to namespaces, deployments, pods, and labels with granular accuracy. Acquired by IBM, it has become the standard for K8s cost visibility. Features include savings recommendations, budget alerts, cluster right-sizing, and multi-cluster cost aggregation across AWS, GCP, and Azure.

Run AI workloads on any cloud with automatic cost optimization

SkyPilot is an open-source framework for running LLMs, AI, and batch jobs on any cloud with automatic cost optimization. It supports AWS, GCP, Azure, Lambda Cloud, and more, automatically selecting the cheapest available GPUs and managing spot instance preemption. Features include multi-cloud job scheduling, managed spot jobs with automatic recovery, and cluster autoscaling with 6,000+ GitHub stars.

AI group-buying for AWS cost reduction

Pump is a YC-backed platform that uses AI and group-buying power to automate AWS cost reduction, claiming up to 60% savings on compute through collective purchasing of Reserved Instances and Savings Plans. By pooling demand across multiple customers, Pump negotiates volume discounts that individual organizations cannot access, providing enterprise-level pricing to startups and mid-market companies.

AI-managed spot instances for production workloads

Xosphere automates the use of AWS Spot Instances for production workloads using ML to select instances based on availability and cost-performance balance. It installs in 10 minutes via CloudFormation and provides high-availability reliability with cheap spot pricing, automatically managing instance selection, interruption handling, and failover for teams wanting significant compute cost savings.

Unified multi-cloud cost management with MegaBill

Finout unifies cloud costs from AWS, Azure, GCP, Snowflake, and other providers into a single MegaBill dashboard with AI-based anomaly detection for flagging unusual spend patterns. Priced at approximately 1% of cloud spend, it solves the multi-tool cost fragmentation problem for organizations managing complex infrastructure budgets across multiple cloud and SaaS providers.

Cloud cost intelligence mapped to business units

CloudZero is a cost intelligence platform that maps cloud spend to engineering teams, product lines, and business units using AI-driven anomaly detection. It provides engineering-friendly insights that help developers understand the cost impact of their code changes, with per-commit cost tracking through CI/CD integration and flexible multi-cloud support across AWS, GCP, and Azure.

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.