AI/LLM Resource Tracking
Simplify TCO & FinOps For AI, GPU & LLM
Amberflo helps enterprises track, optimize, and save on Total Cost of Ownership (TCO) of their enterprise IT footprint, including AI, LLM and Cloud costs. Our modern FinOps for AI platform delivers real-time LLM usage and cost visibility, automated governance, and built-in cost allocation and chargebacks—turning AI roll out and cost management into a driver of efficiency, value and savings.
What is Amberflo AI Gateway?
Integrated LLM Observability and FinOps - Unit Costs, Access, Governance, Chargebacks, Savings, and more
Amberflo AI Gateway is an LLM Gateway that streamlines access to 100+ Large Language Models (LLMs) and distilled LLMs deployed in private clouds or VPCs, through a single, secure, and unified interface. All interactions use the familiar OpenAI API format, eliminating the complexity of managing multiple provider APIs, authentication methods, and response formats. Whether you are using a single LLM provider such as Amazon Bedrock, or multiple ones, Amberflo AI Gateway delivers centralized access, governance, and control with real-time usage, costs allocation, attribution and per unit analytics.
How is Amberflo AI Gateway Different?
Amberflo AI Gateway is part of the Amberflo Enterprise FinOps for AI Platform—a modular suite of services designed to work independently or as an integrated whole, depending on your organization’s current and future needs.
Unlike other gateways that primarily function only as API traffic analyzers, Amberflo AI Gateway comes built-in with a full set of Total Cost of Ownership (TCO) and FinOps capabilities, to serve as a comprehensive, one-stop, integrated FinOps for AI platform. Amberflo FinOps for AI platform delivers a full-featured governance and a cost-management engine for AI and LLM workloads.
Below are some of the core capabilities out-of-the-box of Amberflo FinOps for AI:
i) AI Gateway - Centralized Access with One Standard API for all LLMs (Public Cloud, Direct, and on-prem Distilled)
Manage access by department, application, or user, and track usage and costs in real time across models, versions, providers, and locations.
ii) AI Metering - Automatic LLM Usage Aggregation by Custom Attributes
Built into the Amberflo AI Gateway is Amberflo AI Metering which captures and aggregates requests and responses (input and output tokens) in real time and at scale, across all LLMs, with attribution such as department, application, user, model name, version, and more. Real-Time insights are available via built-in analytics dashboards or via API for seamless 3rd party integration.
iii) LLM Cost and Custom Rates - by App, Dept, Teams, etc
Amberflo’s native rating engine applies either published list prices or fully configurable custom rates by business unit or other entities. Costs are calculated instantly as usage flows through the gateway.
iv) Cost Guards and Budget Tracking
Set granular rules and thresholds by model, application, or version to keep usage and costs under control. Alerts trigger in real time with notifications sent via email or webhook.
v) Showbacks and Chargebacks
Amberflo’s billing engine sits on top of the rating layer, delivering advanced chargeback and billing configurations including budgets, commitments, free tiers, overages, and custom pricing plans. Results can be presented via dashboards, a built-in billing portal, or APIs with full invoice manifests.
vi) Workload Planning and Sizing
Plan new initiatives or optimize existing workloads using a built-in CPQ-style tool. Access a catalog of all LLM models, versions, and public price points, with support for custom or negotiated rates. Generate detailed manifests of services, rates, and projected usage to guide budgeting and forecasting.
Key Features
Universal Model Access
- 100+ Model Support: Access models from OpenAI, Anthropic, AWS Bedrock, Google VertexAI, Azure, Cohere, Hugging Face, Replicate, Groq, and more
- Distilled, Private Cloud Model Support: Unify Public and Private Cloud LLM models FinOps, Governance, and Control
- Unified Interface: Write code once and run it across any supported model provider
- Consistent Format: All responses delivered in standardized OpenAI format
Advanced Usage and Cost Management
- Automatic Spend Tracking: Real-time cost monitoring across all providers and models
- Budget Controls: Set spending limits per project, team, API key, or individual user
- Custom Pricing: Configure your own pricing models for accurate cost attribution
- Usage Analytics: Detailed reporting on tokens, requests, and costs by user, team, or project
Enterprise-Grade Reliability
- Load Balancing: Distribute requests across multiple providers automatically
- Fallback Support: Seamlessly switch to backup providers when primary services fail
- Rate Limiting: Control request rates to prevent service overload
- Health Monitoring: Real-time status checks for all connected model providers
Security & Access Control
- Virtual Keys: Create and manage API keys without exposing provider credentials
- Team-Based Access: Control which models and features each team can access
- Custom Authentication: Integrate with your existing identity management systems
- Audit Trails: Complete logging of all API requests and responses
Comprehensive Observability
- Multi-Platform Logging: Send logs to S3, GCS, Langfuse, Datadog, and more
- Prometheus Metrics: Built-in metrics collection for monitoring and alerting
- Real-Time Dashboard: Web-based UI for monitoring usage, costs, and performance
- Custom Callbacks: Integrate with your existing monitoring and analytics tools
Deployed in Your VPC or On-Prem
- Data Privacy: Complete control over data privacy and security
- 100% Secure: Deploy in your own cloud or on-prem infrastructure
- Full Tenant Isolation: No data mingling.
Business Benefits
Accelerate Development
- Scale existing models or Deploy new models within a day of their release
- Eliminate months of integration work across different providers
- Focus on business logic instead of API management complexity
Reduce Operational Complexity
- Standardize logging, authentication, and API formats across all models
- Centralize model access without distributing individual provider API keys
- Simplify troubleshooting with unified error handling and monitoring
Optimize Costs
- Track granular usage data by user, project, and model
- Set proactive budget controls to prevent overspend
- Compare costs across providers to optimize your model selection
Scale with Confidence
- Handle variable workloads with automatic load balancing and fallbacks
- A/B test different models easily without code changes
- Build robust LLM workflows with built-in retry and error management
Use Cases
Public Cloud and Frontier LLMs and Distilled LLMs in Private Cloud
- Unified and complete FinOps and Governance.
Platform Teams
- Provide standardized LLM access to development teams without managing individual provider relationships
AI Applications
- Build chatbots, content generators, and AI assistants that can seamlessly switch between models
Cost Optimization
- Monitor and control AI spending across large organizations with detailed usage analytics
Multi-Model Workflows
- Create applications that leverage different models for different tasks while maintaining consistent interfaces