# Best Tools to Track AI Spend Across Teams (2026): Compared Canonical: https://www.pointfive.co/guides/finops-tools-for-managing-ai-costs Tools to track and reduce AI and LLM spend across teams in 2026: provider APIs, LLM gateways, observability, FinOps platforms and coding agent tools. By: PointFive Team Published: 2026-07-30 Updated: 2026-10-09 [All guides](https://www.pointfive.co/guides) # Best Tools to Track and Manage AI Spend Across Teams (2026): A Comparison-Driven Guide PointFive Team July 30, 2026 11 min read Disclosure: PointFive wrote this guide, and PointFive is listed first because it is our platform, not because of a ranking. Every competitor statement comes from that vendor's own website, documentation, GitHub repository or press release, checked on October 9, 2026, and linked in the sources. Where a vendor publishes nothing, we say so. ## TLDR - AI spend shows up in five layers: provider usage APIs, LLM gateways, LLM observability, FinOps platforms, and tools for AI agents and coding agents. No single tool covers all five; most companies run two or three. - Tracking spend across teams requires attribution: every request needs an owner (API key, user, team or application). Gateways assign it in the request path; billing tools can only report what you set up. - Pick by gap: LiteLLM, Bifrost, Cloudflare AI Gateway or OpenRouter for per-team budgets; Langfuse or Datadog for cost per request; Vantage or CloudZero for AI spend in FinOps reports. - PointFive is an agentic FinOps platform that puts AI spend next to cloud and data spend and acts on it: PointFive OS attributes and reduces the cost of AI infrastructure and services, and TokenShift sees, controls and coaches the AI agents employees run on their workstations. ## How we evaluated We compared each option on six dimensions, unweighted: - Attribution: which owners it assigns spend to (key, user, team, project, application, model). - Enforcement: alerts only, or budgets and hard limits. - Coverage: model providers, cloud AI services and coding agents. - Position: in the request path, reading billing data, or on the developer endpoint. - Action: reporting only, or help reducing cost. - Pricing model: as publicly stated. ## Why tracking AI spend across teams needs attribution A provider invoice says what the organization spent, not which team spent it. Tracking spend across teams means attaching an owner to every request: a project or API key per team, a user ID, an application tag, or a gateway key mapped to a team budget. Attribution answers who spent it, not whether it was worth it. For that, measure cost per successful task: total spend divided by tasks that actually completed, retries and failures included. A cheaper model that fails twice as often is not cheaper. See [cost per successful task](https://www.pointfive.co/blog/llm-cost-optimization-cost-per-successful-task) and [what FinOps for AI means](https://www.pointfive.co/blog/what-is-finops-for-ai) . ## The tools ### 1. PointFive (PointFive OS and TokenShift) Category: Agentic FinOps platform for cloud, data and AI, plus AI agent governance (layers 4 and 5) Best for: Enterprises that want AI spend attributed and reduced alongside cloud and data spend, including coding agents. PointFive combines two complementary products. [PointFive OS](https://www.pointfive.co/products/pointfive-os) , "The agentic FinOps platform for your cloud, data, and AI", attributes AI cost by model, team, application, developer and token type (input, output, cached, reasoning) across AWS, Azure, GCP, Snowflake, Databricks, OpenAI, Anthropic and endpoint AI tools. It covers Azure OpenAI, Amazon Bedrock, Gemini Enterprise Agent Platform (formerly Vertex AI), GPUs, inference endpoints, Databricks Model Serving, Snowflake Cortex AI and LLM gateways such as LiteLLM and Langfuse, with 500+ deep detections across 40+ [supported platforms](https://www.pointfive.co/coverage) . [TokenShift](https://www.pointfive.co/products/tokenshift) , the AI agent control plane for your employee workstations, covers Claude Code, Codex, Cursor, GitHub Copilot CLI, OpenCode and Devin, with spend by developer, team, model and session. - Strengths: AI, cloud and data spend in one place, with fixes through Chat (with the Pointer agent), Coworkers and Apps. TokenShift lets admins allow or block models, MCP servers, tools and skills, set budgets that warn, block or need approval, and coach people in the moment; Smart Routing is a separate opt-in module. TokenShift installs as a lightweight local binary with no proxy architecture and no IDE plugins, deploys through the MDM you already use, and processes data on the device. Rated 4.9/5 on G2; Nubank saved $8.2M in 9 months with PointFive. - Limitations: No self-serve tier or public price list. Automated remediation requires customer-authorized write permissions and approval, which security teams will want to review. PointFive OS is not an LLM gateway or tracing tool, so apps that need request routing or prompt-level traces still need layer 2 or 3. - Pricing: Custom; contact sales. Also on AWS Marketplace and Azure Marketplace. - Choose it if: You want AI spend across clouds and providers reduced, not only reported, and the AI agents on employee workstations under policy and budget. Layer 1: provider-native data. Each provider sees only its own traffic. ### 2. OpenAI and Anthropic usage and cost APIs (as of October 2026) Category: Provider-native usage and cost reporting Best for: Teams on one or two providers that separate teams by project, workspace or key. OpenAI's Usage API groups usage by project, user, API key, model and batch; its Costs API groups daily cost by project and line item. Both need an admin key. OpenAI projects support spend alerts and an optional hard limit that returns a 429 error. Anthropic's Usage and Cost Admin API groups usage by API key, workspace, model and service tier, and workspaces support monthly spend limits. Its Claude Code Analytics API reports daily per-user Claude Code cost by model. - Strengths: First-party data and real hard limits. - Limitations: One provider each; attribution only as good as your project and key structure. Claude Code Analytics excludes usage through Bedrock, Google Cloud and Microsoft Foundry. - Pricing: Part of the provider platform; Anthropic states Claude Code Analytics is free with Admin API access. - Choose it if: Each team can have its own project, workspace or key. ### 3. Cloud billing for Bedrock, Azure OpenAI and Gemini Enterprise Agent Platform (as of October 2026) Category: Native cloud billing for managed AI services Best for: Teams that consume models through their cloud account. Since April 2026, Amazon Bedrock allocates cost by IAM user and role in CUR 2.0 and Cost Explorer (extended to the bedrock-mantle endpoint in August 2026), and application inference profiles carry cost allocation tags. Microsoft Foundry tags usage per project for chargeback (preview, for models sold by Azure, including Azure OpenAI). Gemini Enterprise Agent Platform (formerly Vertex AI) forwards custom labels on API calls to Cloud Billing. - Strengths: Spend lands in the bill finance already reconciles. - Limitations: One cloud each, with billing delays. Microsoft states Azure OpenAI has no hard spend limit. Google labels apply only to pay-as-you-go requests. - Pricing: Included in cloud billing tools. - Choose it if: Most model spend runs through one cloud. Layer 2: LLM gateways. In the request path, a gateway can tag every call with an owner and stop spend at a budget. ### 4. LiteLLM (as of October 2026) Category: Open-source LLM gateway Best for: Platform teams that want self-hosted per-team budgets across 100+ model APIs. LiteLLM tracks spend by key, user, team, end user and tag. Budgets with reset windows apply per virtual key, user, team, team member and end customer; requests fail once a budget is exceeded. - Strengths: Widely adopted (60,000+ GitHub stars); budget hierarchy maps to org structure. - Limitations: Budgets require a database; some features, such as per-model budgets, are Enterprise. In March 2026, two malicious releases (1.82.7 and 1.82.8) briefly reached PyPI; pin and verify versions. - Pricing: Open source free; Enterprise custom. - Choose it if: You can run the gateway yourself. ### 5. Portkey, now part of Palo Alto Networks (as of October 2026) Category: AI gateway inside Prisma AIRS Best for: Enterprises pairing gateway budgets with AI security. Palo Alto Networks completed its Portkey acquisition on May 29, 2026, making it "the core AI Gateway for Prisma AIRS". Portkey supports cost- and token-based budget limits with alert thresholds and weekly or monthly resets. - Strengths: Budgets in dollars or tokens; security roadmap through Prisma AIRS. - Limitations: Budget limits are Enterprise and select Pro only; direction now follows Palo Alto Networks. - Pricing: Developer free; Production $49/month; Enterprise custom. - Choose it if: You are standardizing on Palo Alto Networks. ### 6. Bifrost by Maxim (as of October 2026) Category: Open-source AI gateway (Apache 2.0) Best for: Hierarchical budgets in a self-hosted gateway. Bifrost enforces budgets at customer, team, virtual key and provider-config levels, and "all applicable budgets must pass" before a request proceeds. A provider over budget drops out of routing instead of failing the request. - Strengths: Clear budget hierarchy; calendar-aligned resets. - Limitations: High availability is Enterprise-only. - Pricing: Open source free; Enterprise not published. - Choose it if: You need per-team and per-customer budgets you host. ### 7. Cloudflare AI Gateway (as of October 2026) Category: Managed AI gateway Best for: Teams already on Cloudflare. AI Gateway estimates cost from tokens and enforces dollar spend limits per provider, model or custom metadata, split per user. Over-budget requests get a 429 error or fall back to a cheaper model through Dynamic Routing. - Strengths: Per-user budgets with no infrastructure to run. - Limitations: Cost is "an estimation"; limits are eventually consistent, so bursts can briefly exceed them. - Pricing: Core features free on all plans; 5% fee on Unified Billing credits. - Choose it if: You want a managed gateway with per-user budgets. ### 8. OpenRouter (as of October 2026) Category: Hosted model router with unified billing Best for: Buying many models through one account. OpenRouter returns cost with every response, and guardrails set daily, weekly or monthly budgets per member and per API key. Organization activity can be filtered by key. - Strengths: One bill across providers; member and key budgets. - Limitations: Sees only traffic routed through it; workspace budgets are Enterprise. - Pricing: Provider list price with no markup; 5.5% platform fee on credit purchases (8% Business); BYOK free up to $25,000/month of usage, then 5%. - Choose it if: You want per-member caps across many models. Layer 3: LLM observability. Cost per request, trace and user inside an application. Helicone joined Mintlify in March 2026 and is in maintenance mode. See [open-source LLM observability tools](https://www.pointfive.co/blog/open-source-llm-observability-tools) . ### 9. Langfuse (as of October 2026) Category: Open-source LLM engineering platform Best for: Cost per trace, user and feature next to evaluations. Langfuse ingests or infers cost per generation and shows it by model, user and tag, with spend alerts. ClickHouse acquired Langfuse in January 2026; core features stay MIT licensed. - Strengths: Cost tied to traces, prompts and evals; free self-hosting. - Limitations: Alerts, not budget enforcement. - Pricing: Hobby free; Core $29/month; Pro $199/month; Enterprise $2,499/month. - Choose it if: You need to know which feature or prompt drives cost. ### 10. Datadog Agent Observability, formerly LLM Observability (as of October 2026) Category: LLM and agent observability inside Datadog Best for: Teams already on Datadog. Datadog estimates cost per LLM call for OpenAI, Anthropic, Gemini, Hugging Face and OpenRouter models, broken down by model, prompt version, token type and custom tags such as team. - Strengths: AI cost next to APM and infrastructure data. - Limitations: Estimates, not invoices. - Pricing: Free up to 40K LLM spans/month; Pro from $160/month (annual) with 100K spans. - Choose it if: Datadog is your observability standard. Layer 4: FinOps platforms. These import billing data and put AI spend next to cloud spend. ### 11. Vantage (as of October 2026) Category: Cost visibility and allocation for cloud, SaaS and AI Best for: Self-serve AI cost reporting. Vantage imports OpenAI costs by project and model, Anthropic costs by workspace, API key and model, and Cursor spend by developer and model. Since September 10, 2026, it imports Codex costs for OpenAI Enterprise customers. - Strengths: Free tier; budgets and anomaly detection. - Limitations: Reads billing data; does not enforce limits at the provider. Self-serve tiers cap tracked spend. - Pricing: Starter free (up to $2,500 tracked); Pro $30/month; Business $200/month; Enterprise custom. - Choose it if: You want to start without a sales cycle. ### 12. CloudZero (as of October 2026) Category: Cost allocation and unit economics, positioned around AI Best for: AI cost by person, team and type of work. CloudZero calls itself a "financial control plane for AI economics". AI Signals (September 23, 2026) attributes AI spend by person, team and work done across Anthropic, OpenAI, Google Vertex and Gemini, AWS Bedrock, Fireworks, LiteLLM, Bifrost and OpenTelemetry. A Cursor connection adds cost by user and model. - Strengths: Attribution to business activities; Slack and email monitors. - Limitations: No public pricing; does not enforce budgets at the provider. - Pricing: "A single subscription with all capabilities included"; custom quote. - Choose it if: Finance needs AI cost per team or initiative. Layer 5: AI agents and coding agents. Coding agent subscriptions often bypass gateways. Billing imports (Vantage, CloudZero, Claude Code Analytics) show per-user spend after the fact; TokenShift (entry 1) runs on the developer's workstation and enforces budgets while the agent runs, alongside your gateway. ## Side-by-side comparison | Tool | Layer | Attributes spend to | Enforces budgets | Coding agents | Open source | Public pricing | | --- | --- | --- | --- | --- | --- | --- | | PointFive | FinOps platform, agent control | Model, team, app, developer, token type, session | Warn, block or approval (TokenShift) | Claude Code, Codex, Cursor, GitHub Copilot CLI, OpenCode, Devin (TokenShift, on workstations) | No | No (custom) | | OpenAI / Anthropic APIs | Provider | Project or workspace, key, user, model | Yes, hard limits | Claude Code (Anthropic) | No | Included | | Cloud billing | Provider | IAM principal, tag, project, label | Budget alerts; Azure states no hard limit | No | No | Included | | LiteLLM | Gateway | Key, user, team, end user, tag | Yes | If routed | Yes | Model only | | Portkey | Gateway | Provider, workspace | Enterprise | If routed | Gateway | Yes | | Bifrost | Gateway | Customer, team, virtual key | Yes | If routed | Yes | OSS free | | Cloudflare AI Gateway | Gateway | Provider, model, metadata, user | Yes | If routed | No | Yes | | OpenRouter | Gateway | Member, key, model | Yes | If routed | No | Yes | | Langfuse | Observability | Model, user, tag | Alerts only | No | Yes | Yes | | Datadog | Observability | Model, prompt, custom tags | Not documented | No | No | Yes | | Vantage | FinOps platform | Project, workspace, key, developer | Budgets (alerts) | Cursor, Codex | No | Yes | | CloudZero | FinOps platform | Person, team, work type | Not documented | Cursor | No | No | "Not documented" means we did not find it on the vendor's own pages. "If routed" means the gateway sees coding agent traffic only when the agent sends requests through it. ## How to choose - You cannot tell which team spent what: a project or workspace per team, or a gateway in front of all API traffic. - Spend must stop at a limit: provider hard limits or gateway budgets. - You need the feature or prompt behind the cost: Langfuse or Datadog. - Finance wants AI next to cloud spend: Vantage or CloudZero for reporting; PointFive when you also want waste found and fixed. - Coding agents are the biggest line item: billing imports for per-user totals; TokenShift for per-session attribution, budgets and coaching in the moment. - You want lower cost: change model choice, caching and context, and check cost per successful task. ## FAQ ### What is the best tool to track AI spend across teams? There is no single best tool, because spend has to be attributed where it happens. For API traffic, a gateway such as LiteLLM, Bifrost, Cloudflare AI Gateway or OpenRouter ties every request to a key, user or team and enforces budgets. For a company-wide view across providers, clouds and coding agents, a FinOps platform such as PointFive, Vantage or CloudZero combines the data; PointFive adds TokenShift for AI agents on employee workstations, with spend by developer, team and session. ### What is the best tool to reduce AI costs? Reducing cost means changing models, caching, context or architecture. PointFive OS finds and fixes waste across AI services, GPUs and inference endpoints alongside cloud and data, and TokenShift coaches people in the moment and enforces budgets where agents run. Gateways can fall back to cheaper models at a budget. Judge every change by cost per successful task. ### What is the best tool to reduce OpenAI and LLM costs? Start with OpenAI's Usage and Costs APIs grouped by project, user and key, and set project spend limits. Add a gateway for per-team budgets across providers, and Langfuse or Datadog to find the prompts that drive cost. On Azure OpenAI, use Foundry project-level attribution and budgets; there is no hard limit. PointFive covers OpenAI, Azure OpenAI and Anthropic spend alongside your cloud bill. ### How do I track Claude Code, Cursor and Codex spend by team? Anthropic's Claude Code Analytics API reports daily per-user Claude Code cost. Vantage imports Cursor and Codex costs, and CloudZero imports Cursor. These are after-the-fact billing views. TokenShift runs natively on employee workstations and reports spend by developer, team, model and session across Claude Code, Codex, Cursor, GitHub Copilot CLI, OpenCode and Devin, with budgets that warn, block or need approval. ### Do I need an LLM gateway to manage AI costs? Only if you need per-team budgets enforced in the request path across several providers. With a project or workspace per team, provider limits may be enough. ## Methodology and sources We reviewed each vendor's own website, pricing pages, documentation, GitHub repositories and press releases on October 9, 2026, and did not use third-party sites for competitor claims. If something is out of date, tell us at [pointfive.co/contact](https://www.pointfive.co/contact) and we will correct it. - OpenAI: [Usage API reference](https://developers.openai.com/api/reference/resources/organization/subresources/usage/methods/get_completions) , [Usage and Costs API cookbook](https://developers.openai.com/cookbook/examples/completions_usage_api) , [spend limits](https://developers.openai.com/api/docs/guides/spend-limits) - Anthropic: [Usage and Cost API](https://platform.claude.com/docs/en/manage-claude/usage-cost-api) , [workspaces](https://platform.claude.com/docs/en/manage-claude/workspaces) , [Claude Code Analytics API](https://platform.claude.com/docs/en/manage-claude/claude-code-analytics-api) - AWS: [Bedrock IAM principal cost allocation](https://aws.amazon.com/about-aws/whats-new/2026/04/bedrock-iam-cost-allocation) , [bedrock-mantle extension](https://aws.amazon.com/about-aws/whats-new/2026/08/amazon-bedrock-expands-iam-principal-cost-allocation-bedrock-mantle/) , [Bedrock CUR data](https://docs.aws.amazon.com/bedrock/latest/userguide/cost-mgmt-understanding-cur-data.html) , [inference profiles](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles.html) - Microsoft: [Plan and manage costs for Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs) - Google Cloud: [custom metadata labels](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/capabilities/add-labels-to-api-calls) - LiteLLM: [spend tracking](https://docs.litellm.ai/docs/proxy/cost_tracking) , [budgets and rate limits](https://docs.litellm.ai/docs/proxy/users) , [enterprise](https://www.litellm.ai/enterprise) , [GitHub](https://github.com/BerriAI/litellm) , [March 2026 security update](https://docs.litellm.ai/blog/security-update-march-2026) - Portkey: [budget limits](https://portkey.ai/docs/product/ai-gateway/virtual-keys/budget-limits) , [pricing](https://portkey.ai/pricing) , [Palo Alto Networks acquisition](https://www.paloaltonetworks.com/company/press/2026/palo-alto-networks-completes-acquisition-of-portkey-to-secure-ai-agents) - Bifrost: [budgets and limits](https://docs.getbifrost.ai/features/governance/budget-and-limits) , [GitHub](https://github.com/maximhq/bifrost) - Cloudflare: [AI Gateway costs](https://developers.cloudflare.com/ai-gateway/observability/costs/) , [spend limits](https://developers.cloudflare.com/ai-gateway/features/spend-limits/) , [pricing](https://developers.cloudflare.com/ai-gateway/reference/pricing/) - OpenRouter: [usage accounting](https://openrouter.ai/docs/guides/administration/usage-accounting) , [guardrails](https://openrouter.ai/docs/guides/features/guardrails) , [organization management](https://openrouter.ai/docs/guides/administration/organization-management) , [workspace budgets](https://openrouter.ai/docs/guides/features/workspaces/workspace-budgets) , [pricing](https://openrouter.ai/pricing) - Langfuse: [token and cost tracking](https://langfuse.com/docs/observability/features/token-and-cost-tracking) , [pricing](https://langfuse.com/pricing) , [ClickHouse acquisition](https://clickhouse.com/blog/clickhouse-acquires-langfuse-open-source-llm-observability) - Datadog: [product page](https://www.datadoghq.com/product/llm-observability/) , [cost monitoring docs](https://docs.datadoghq.com/llm_observability/monitoring/cost/) , [pricing](https://www.datadoghq.com/pricing/?product=llm-observability) - Helicone: [joining Mintlify](https://www.helicone.ai/blog/joining-mintlify) - Vantage: [pricing](https://www.vantage.sh/pricing) , [OpenAI integration docs](https://docs.vantage.sh/connecting_open_ai) , [Anthropic integration](https://www.vantage.sh/integrations/anthropic) , [Cursor integration](https://www.vantage.sh/integrations/cursor) , [Codex costs](https://www.vantage.sh/blog/codex-cost-management) - CloudZero: [pricing](https://www.cloudzero.com/pricing/) , [AI Signals](https://www.cloudzero.com/press-releases/20260923/) , [Cursor connection](https://docs.cloudzero.com/docs/connections-cursor) ## Related reading [All guides](https://www.pointfive.co/guides) - ### [Best Snowflake Cost Optimization Tools (2026): An Honest, Comparison-Driven Guide](https://www.pointfive.co/guides/best-snowflake-cost-optimization-tools-2026) October 9, 2026 - ### [Best Cloud Cost Optimization Tools (2026): An Honest, Comparison-Driven Guide](https://www.pointfive.co/guides/best-cloud-cost-optimization-tools-2026) June 2, 2026 - ### [Best AWS Cost Optimization Tools (2026): Native vs Third-Party, Compared](https://www.pointfive.co/guides/best-aws-cost-optimization-tools-2026) October 9, 2026 --- Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.