> For the complete documentation index, see [llms.txt](https://docs.onelens.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.onelens.cloud/solutions/ai-cost-governance.md). # AI Cost Governance > Gain complete visibility into AI spending, optimize costs, automate operations, and enforce governance across every AI provider from a single platform. AI Cost Governance brings together observability, optimization, automation, and governance into a unified platform. Whether you're using OpenAI, Anthropic, Amazon Bedrock, Azure AI Foundry, Vertex AI, or multiple providers, OneLens helps you understand where your AI budget is going, identify savings opportunities, and establish organization-wide controls. *** ### Why AI Cost Governance? As AI adoption grows, managing costs becomes increasingly complex. Organizations often struggle with: * AI spend spread across multiple providers * No visibility into which teams or applications own costs * Budget overruns discovered only after invoices arrive * Expensive models being used unnecessarily * Difficulty allocating AI costs to products or customers * Limited governance over AI usage OneLens provides a centralized platform to monitor, optimize, and govern AI spend across your entire organization. *** ### One Unified Platform Instead of using separate tools for reporting, budgeting, optimization, and governance, OneLens brings everything together in a single platform. The platform is built around four key pillars: | Pillar | Description | | ------------ | ---------------------------------------------------------------------------------------- | | **Observe** | Analyze AI costs, usage, tokens, and workloads across all providers. | | **Optimize** | Identify cost-saving opportunities across models, tokens, infrastructure, and workloads. | | **Automate** | Generate reports, detect anomalies, and notify teams automatically. | | **Govern** | Enforce budgets, controls, policies, and accountability across the organization. |
*** ## Observe Gain complete visibility into AI costs and usage across your organization. Capabilities include: * AI Cost & Usage Analyzer * AI Cost Allocation * Unit Metrics * AI Cost Anomalies * Custom Dashboards * Saved Reports * Advanced Filters * Multi-level Group By Quickly understand: * Which teams are spending the most * Which models drive costs * How token usage changes over time * Which customers or products generate AI costs
*** ## Optimize Continuously identify opportunities to reduce AI costs without impacting application quality. Optimization recommendations include: * Model right-sizing * Prompt cache optimization * Output token optimization * Batch API opportunities * Idle provisioned throughput * Endpoint right-sizing * Fine-tuned model utilization * Workload-specific recommendations Every recommendation includes estimated savings and implementation guidance.
*** ## Automate Reduce manual effort by automating reporting, monitoring, and notifications. Automate: * AI Summary Reports * Cost Change Reports * Anomaly Notifications * Budget Alerts * Executive Reports * Workflow Notifications Deliver updates directly through Email, Slack, Microsoft Teams, or ServiceNow. *** ## Govern Ensure AI adoption remains secure, accountable, and financially sustainable. Govern AI usage with: * AI Budgets * Budget Utilization Tracking * Pro-rata Forecasting * AI Controls * Model Governance * Spending Limits * Policy-Based Controls * Audit History Keep every team accountable while maintaining centralized visibility across the organization. *** ### Multi-Provider Support OneLens normalizes billing and usage data across multiple AI providers into a single reporting model. Supported providers include: * OpenAI * Anthropic Claude * Amazon Bedrock * Azure AI Foundry * Google Vertex AI * Google Gemini * LiteLLM * OpenRouter This enables consistent reporting, dashboards, and governance regardless of where your AI workloads run. *** ### Built for Every Team #### Engineering * Monitor application-level AI costs * Optimize model usage * Investigate anomalies * Improve workload efficiency #### Platform & FinOps * Track AI spending across providers * Allocate costs accurately * Identify optimization opportunities * Improve operational visibility #### Finance * Forecast AI spend * Track budgets * Allocate costs by business unit * Measure AI COGS #### Product * Understand AI cost per feature * Measure unit economics * Track customer profitability * Build sustainable pricing strategies *** ### Enterprise Capabilities In addition to core AI cost governance, OneLens provides: * Custom Dashboards * Saved Reports * Scheduled Reports * Advanced Filters * Up to 4-Level Group By * Cost Allocation * Budget Management * Workflow Automation * Email & Slack Notifications * ServiceNow Integration * Role-Based Access Control (RBAC) * Audit Logs *** ### Privacy First OneLens is designed with a privacy-first architecture. The platform only accesses billing and usage metadata required for cost governance. OneLens **never** collects: * Prompts * Conversations * Model responses * Uploaded files * Embeddings * Training datasets Your AI data remains within your environment while OneLens provides complete visibility into costs and usage. *** ### Benefits * Centralize AI cost management across providers. * Improve visibility into AI spending and usage. * Reduce AI costs through actionable optimization recommendations. * Detect unexpected cost spikes automatically. * Allocate AI costs to teams, products, and customers. * Enforce budgets and governance policies. * Improve collaboration between engineering, finance, and leadership. * Scale AI adoption with confidence. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.onelens.cloud/solutions/ai-cost-governance.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.