Mavvrik
Mavvrik is an AI and hybrid infrastructure cost management platform that gives finance, FinOps, IT, and engineering teams one control center for GenAI, autonomous agents, GPUs, cloud, on-premises systems, Kubernetes, data platforms, and SaaS. It unifies cost, usage, and telemetry signals from AWS, Azure, Google Cloud, Oracle, VMware, NVIDIA, OpenAI, Anthropic, Gemini, Snowflake, Databricks, and LiteLLM, creating a single source of truth across the technology stack. Teams can track every model call, agent interaction, GPU hour, workload, service, and resource, then allocate spending by customer, product, feature, project, application, environment, team, or cost center. Cost-to-serve and unit-economics analysis reveal margin drains, expensive workloads, and the true cost of delivering each offering. Real-time anomaly detection and alerts identify usage before it becomes a budget surprise, while predictive forecasting helps organizations model cloud, GPU, and AI expenses.
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AICosts.ai
AICosts.ai is a unified AI cost management platform that brings billing and usage data from more than 50 providers into one dashboard. Teams upload provider invoices and exports in PDF, CSV, or JSON format, or push usage events through the developer API, and the platform parses them into a normalized structure without requiring a proxy or changes to production requests. It supports services including OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Vertex AI, Cohere, Groq, Hugging Face, Pinecone, RunwayML, Make, Zapier, and n8n. Daily views break spending down by platform, model, and billed unit, including tokens, operations, characters, and other provider-specific measures, helping users compare services and see where each bill comes from. Budgets can cover the full AI stack or a specific platform or feature, with email alerts when rolling 30-day spending crosses configured thresholds.
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Cloudgov.ai
Cloudgov.ai is an agentic AI FinOps platform for continuous cost and policy governance across cloud, multicloud, data, container, and AI environments. It brings AWS, Azure, Google Cloud, Oracle Cloud, Snowflake, Databricks, Kubernetes, OpenAI, Anthropic, and Gemini into one control plane, giving teams a live view of cost, allocation, policy, and risk. Continuous Multicloud Observability connects accounts, analyzes historical spending, filters costs by region, account, and service, and forecasts future spend from history. AI-driven insights identify waste and optimization opportunities, while anomaly detection highlights unexpected spending surges and their financial impact. Ready-to-use Infrastructure as Code remediation snippets help engineering teams apply recommended changes, and Jira integration turns insights and anomalies into assignable work.
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LLMetrics
LLMetrics is LLM cost tracking software for teams shipping AI products, bringing model spend, token usage, feature attribution, and usage alerts into one live dashboard. It supports more than 100 models across OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Together AI, Groq, and other providers, with pricing data synchronized daily. Teams tag each model call with a feature name, provider, model, input tokens, and output tokens, allowing them to see exactly whether a chatbot, summarizer, search feature, lesson generator, or other workflow is driving spend. Real-time updates and daily trend charts reveal how costs change after releases, prompt edits, traffic growth, or model swaps. Spend thresholds and spike-detection rules can alert teams through email or Slack when usage patterns look wrong, helping them catch runaway loops and unexpected cost increases before the provider invoice arrives.
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