Cloud and AI Carbon Emissions: accurate measurement, effective reductions

Tailpipe measures the carbon footprint of your cloud infrastructure and AI workloads — giving you the data to report accurately and reduce effectively.

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Now tracking AI carbon emissions

Route your LLM API traffic through Tailpipe's proxy: set your base URL and add a telemetry header. No code changes for Claude Code, and a one-line config for the SDKs. Supports OpenAI, Anthropic, Gemini, and Mistral, and never captures your prompts or responses.

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from openai import OpenAI

# Change base_url and add the Tailpipe telemetry header
client = OpenAI(
    base_url="https://<your-proxy-url>/openai/v1",
    default_headers={"x-tailpipe-api-key": "tp_your_key_here"},
)
# Telemetry captured automatically

Why Tailpipe?

Recommendations

Actionable insights to reduce your cloud carbon footprint with specific, prioritised recommendations.

Accuracy

Real-time data from your actual cloud usage — not estimates or averages. Methodology verified by independent experts.

Comprehensiveness

Coverage across AWS, Azure, and GCP. Track compute, storage, networking, and now AI workloads in one place.

Transparency

Open methodology aligned with the GHG Protocol and SCI-AI specification. Full auditability for compliance reporting.

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Understanding Cloud Carbon Measurement

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Get started with a free emissions estimate for your cloud infrastructure.

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