
Most enterprises can report what AI cost them. Far fewer can say which team owns it, whether it was approved, or what it returned.
FinOpsly closes that gap. The platform governs AI spend on the same cost model that carries the cloud, data platform and SaaS an AI workload consumes, so a business unit sees the full cost of an AI initiative instead of four disconnected bills.
Capabilities include:
Cost estimation before deployment. Model an architecture and get a priced workload across model APIs, GPU capacity, warehouse consumption and storage, with the assumptions on screen. Weigh model choices against consumption you have actually measured.
Attribution that holds up in a chargeback cycle. Spend resolves to owners, teams, applications, business units and customers through hierarchies nine or more levels deep. Tagging is standardized across providers, keys and resources are labeled in bulk from plain-language rules, and whatever remains unattributed is published as a number, not absorbed.
Guardrails that act. Set budgets by project, team or API key. Catch anomalies with root cause and route them to whoever owns the resource. Surface waste that provider tooling misses, using FinOpsly's own detection models. Plan commitments across AWS, Azure and Google Cloud. Park idle compute on approved schedules, reversibly.
Financial results you can defend. Automated chargeback in a single cycle. Savings measured as what reached run-rate against a no-action baseline. Unit economics down to cost per call, per active user and per customer served.
For technology and finance leaders accountable for what AI spend returns.
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CloudZero helps businesses optimize cloud spend with full visibility into costs—so they can reduce wasteful spending and improve their unit economics. Unlike other solutions, we take an engineering-led approach to cost optimization, helping teams understand what drives 100% of their operational cloud spend, empowering them to reduce risk, minimize waste, and maximize profit.
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LLMeter
LLMeter is a comprehensive open-source platform designed for monitoring AI costs, allowing developers to manage their expenditures across various providers like OpenAI, Anthropic, DeepSeek, OpenRouter, Mistral, and Azure OpenAI from a single dashboard. By simply connecting read-only provider keys, teams can instantly access detailed insights into actual costs, daily usage trends, model-specific analytics, and potential areas for optimization, all within approximately 30 seconds and without any need for SDK installation, endpoint modifications, or rerouting production traffic through a proxy. Since it facilitates direct communication with model providers, LLMeter introduces no additional latency, avoids becoming a single point of failure, and does not access or store any user prompts or completions. Additionally, budget alerts notify teams prior to exceeding their daily or monthly spending thresholds, while anomaly detection features help catch unexpected usage surges before they escalate. The platform's dashboard provides a clear overview of the costs associated with various providers, models, endpoints, customers, and environments, and its integration with OpenRouter enhances transparency by covering over 500 models, ensuring users have a robust tool for managing their AI-related expenditures efficiently. Ultimately, LLmeter empowers teams to make informed financial decisions regarding their AI usage.
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Gravitee
Gravitee is an enterprise platform for managing AI agents, APIs, event streams, and model interactions through a centralized security and governance layer. Its AI Gateway provides three primary entry points through an LLM Proxy, MCP Proxy, and A2A Proxy for governing model access, agent tools, and agent-to-agent communication. The platform can assign and verify agent identities, enforce least-privilege policies, and control which tools, services, and MCP servers individual agents are permitted to use. Security controls include authentication, authorization, PII filtering, API key protection, rate limiting, spending limits, and complete audit trails for AI activity. Gravitee also tracks LLM usage and costs so organizations can understand token consumption, control unplanned spending, and attribute AI usage across users and agents. Its observability features help teams monitor agent behavior, dependencies, traffic flows, and potentially risky or ungoverned interactions. The platform extends these capabilities to conventional APIs and event infrastructure, including REST, GraphQL, gRPC, Kafka, and other enterprise integration technologies. Organizations can also productize internal APIs, MCP tools, workflows, and event streams so they can be securely reused by developers, partners, and AI agents. Gravitee is intended for enterprises, platform teams, security organizations, and AI engineering groups that need a common management layer for agent security, API governance, observability, and AI infrastructure.
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