AI Observatory
AI spend isn't a single line item — it's Anthropic models running via AWS Bedrock, Azure OpenAI alongside direct OpenAI API calls, Gemini, Grok, Qwen, and a dozen other models procured through different channels, billed in different formats, and invisible to any single reporting surface.
AI Observatory is Ternary's global dashboard for AI spend and token usage — a single, governed view across every AI provider, vendor, model family, and version in your technology portfolio. The dashboard is continuously updated to reflect the latest models as they come to market.
How It Works: The Unified AI Schema
Powering the AI Observatory is a provider-agnostic framework that normalizes AI-specific data from every source into a standardized schema. This enables consistent querying, reporting, and analysis regardless of where the spend originates.
Every record is attributed by:
- Provider
- Publisher
- Modality
- Input/output tokens
- Model
- Version
This means Claude, ChatGPT, OpenAI's reasoning models, Whisper, Moonshot Kimi, xAI Grok, Alibaba Qwen, Zhipu GLM, MiniMax, Amazon Nova and Titan — and more — all show up in one place, in the same format.
What You Can Do With It
- Cloud Provider AI Analysis — Break down AI spend procured via GCP, AWS, and Azure, with vendor- and model-level attribution across Anthropic, OpenAI, Google, Meta, and more.
- AI Guardrails — Create budgets and alerts around token usage and cost by model, provider, or any dimension. Control what happens at the point of consumption, not after the invoice arrives.
- Allocate, Showback, and Chargeback — Use Ternary's Billing Rules Engine to attribute AI spend directly to the teams, products, and cost centers that incurred it.
- Custom Labels — Existing label rules apply to AI spend automatically. Create new labels to organize AI investment in ways that map to your business.
Beyond the Dashboard
AI Observatory is a starting point, not a ceiling. Every report underlying the dashboard is available in the Ternary Reporting Engine, ready to be filtered, grouped, and customized to reflect the specific dimensions, models, and cost structures that matter to your business. The same AI-specific data points can be pulled into any report you build in Ternary, not just the Observatory dashboard itself.
Supported Providers
| Publisher | Model families | Providers |
|---|---|---|
| Anthropic | Claude | Anthropic (Direct API / Enterprise), AWS Bedrock, GCP Vertex AI, Azure AI Foundry, Snowflake Cortex |
| OpenAI | GPT / ChatGPT, o-series, Whisper, TTS, embeddings, GPT Image | OpenAI (Direct API), Azure AI Foundry, AWS Bedrock (gpt-oss), GCP Vertex AI, Snowflake Cortex |
| Gemini, Veo, Imagen, embeddings | GCP Gemini API, GCP Vertex AI | |
| Amazon | Nova, Titan | AWS Bedrock |
| Meta | Llama | AWS Bedrock, Azure AI Foundry, GCP Vertex AI, Snowflake Cortex |
| Mistral AI | Mistral | AWS Bedrock, Azure AI Foundry, GCP Vertex AI, Snowflake Cortex |
| Cohere | Command, Rerank | AWS Bedrock, Azure AI Foundry, GCP Vertex AI |
| DeepSeek | DeepSeek V/R series | AWS Bedrock, Azure AI Foundry, GCP Vertex AI, Snowflake Cortex |
| xAI | Grok | AWS Bedrock, Azure AI Foundry, GCP Vertex AI |
| Moonshot AI | Kimi | AWS Bedrock, Azure AI Foundry, GCP Vertex AI |
| Alibaba Cloud | Qwen | AWS Bedrock, Azure AI Foundry, GCP Vertex AI |
| Zhipu AI | GLM | AWS Bedrock, Azure AI Foundry, GCP Vertex AI |
| MiniMax | MiniMax | AWS Bedrock, Azure AI Foundry, GCP Vertex AI |
Updated about 14 hours ago
