AI-native FinOps Solutions by MetaFinOps

Token Cost Intelligence Across Every AI Provider

Track, attribute, and optimize token spend across OpenAI, Anthropic, Google Vertex AI, Cohere, Mistral, and self-hosted models — all in one dashboard.

OpenAI Anthropic Google Vertex Cohere Mistral Self-hosted

Token Costs Are the New Cloud Bill

Multi-provider sprawl

Teams use GPT-4, Claude, Gemini, and open-source models simultaneously. Costs fragment across dozens of API keys and billing accounts.

No per-customer attribution

You know the total monthly LLM bill, but can't tell which customer, feature, or experiment drove 40% of the cost.

Prompt inefficiency is invisible

Verbose prompts, unnecessary system messages, and unoptimized context windows burn tokens silently. There's no feedback loop.

Full-Stack Token Cost Visibility

MetaFinOps captures every API call, maps it to a customer and feature, and surfaces optimization opportunities automatically.

Track prompt tokens, completion tokens, embedding calls, and fine-tuning costs in a unified dashboard. Set per-team and per-customer token budgets with real-time alerts.

Compare cost-per-quality across providers: is GPT-4 Turbo worth 3x the cost of Claude 3 Haiku for your use case? Our model comparison engine answers that with data.

Token Intelligence Capabilities

Multi-Provider Tracking

Unified view of token spend across OpenAI, Anthropic, Google, Cohere, Mistral, and any OpenAI-compatible API. One dashboard for all LLM costs.

Per-Customer Attribution

Map every token to a specific customer, tenant, or business line. Know exactly what each user costs you in AI infrastructure.

Cost-per-Conversation

Track the total token cost of each conversation, session, or workflow. Identify expensive interaction patterns and optimize them.

Token Budget Alerts

Set per-team, per-project, and per-customer token budgets. Get Slack/PagerDuty alerts when spend approaches thresholds.

Prompt Optimization Insights

Identify verbose prompts, redundant system messages, and oversized context windows. Get actionable recommendations to reduce token waste.

Multi-Model Cost Comparison

Compare cost-per-quality across models. Find where cheaper models deliver equivalent results and where premium models justify the cost.

Token Cost Dashboard

Cost by Provider (Monthly)
OpenAI (GPT-4 Turbo)$6,420
Anthropic (Claude 3.5)$3,280
Google (Gemini Pro)$1,850
Self-hosted (Llama 3)$920
Top Customers by Token Spend
Acme Corp (Enterprise)$2,140/mo
TechStart Inc$1,680/mo
DataFlow AI$1,240/mo
Optimization Opportunities
Save $840/mo — Switch FAQ bot from GPT-4 to Claude Haiku
Save $520/mo — Reduce system prompt from 2.1K to 800 tokens
Save $310/mo — Cache embeddings for repeated queries

How Token Cost Is Calculated

Token Cost = (Prompt Tokens × Input Price) + (Completion Tokens × Output Price)
Customer Cost = ∑ Token Cost per Request × Customer Attribution Weight

MetaFinOps captures input/output token counts per API call, multiplies by provider-specific pricing (updated in real-time), and attributes costs using your tagging rules — by customer, feature, team, or experiment.

A SaaS company using MetaFinOps Token Intelligence discovered that 30% of their LLM spend came from a single verbose system prompt. By optimizing it, they saved $1,200/month while maintaining the same output quality.

Start Tracking Your Token Costs

Get visibility into every token across every provider. See optimization opportunities in minutes.

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