What is GateFlow?

GateFlow is an AI Gateway that sits between your application and AI providers like OpenAI, Anthropic, Google, Mistral, and Cohere. It provides a unified API for all your AI needs while adding reliability, observability, and cost control.

The Problem

Building sustainable AI applications is challenging:

• Carbon Intensive Compute: AI models consume massive energy with high carbon footprints
• Inefficient Routing: Requests go to providers without considering carbon impact
• Wasteful Duplication: Same queries executed repeatedly without caching
• No Sustainability Insights: No visibility into carbon emissions per request
• Static Infrastructure: Can't adapt to grid carbon intensity changes

The Solution

GateFlow solves these problems with a single integration:

Key Features

Sustain Mode

Automatically route requests to minimize carbon emissions while maintaining quality requirements. Set minimum quality thresholds and let GateFlow handle the rest.

# Enable Sustain Mode for carbon-optimized routing
response = client.chat.completions.create(
    model="auto",
    routing_mode="sustain_optimized",
    minimum_quality_score=85,
    messages=[{"role": "user", "content": "Analyze this sustainably"}]
)

Intelligent Carbon-Aware Routing

Route requests based on real-time grid carbon intensity, model efficiency scores, and task requirements. Automatic fallbacks to most sustainable available models.

Time-Shifted Execution

Defer non-urgent requests to execute during periods of lower grid carbon intensity, reducing emissions by up to 80%.

Multi-Provider Sustainability

Unified API with sustainability optimization across:

• OpenAI, Anthropic, Google, Mistral - General AI models
• Cohere - Efficient chat, embeddings, and rerank models
• ElevenLabs - Low-carbon voice synthesis

Sustainability Dashboard

Real-time carbon footprint tracking, emissions reporting, and efficiency analytics for all your AI requests.

Semantic Caching with Carbon Savings

Cache similar queries to eliminate duplicate computations, reducing carbon footprint by up to 90% on repetitive requests.

Unified API

One endpoint for every AI provider. Use the OpenAI SDK format you already know, route to any model.

# Same code, any model
response = client.chat.completions.create(
    model="claude-3-5-sonnet",  # Or gpt-4o, gemini-1.5-pro, etc.
    messages=[{"role": "user", "content": "Hello"}]
)

Intelligent Routing

Route requests based on task type, cost, latency, or custom rules. Automatic fallbacks when providers fail.

Model Change Management

When OpenAI deprecates gpt-4-32k, GateFlow automatically falls back to your configured replacement. No code changes needed.

Voice & Audio

Unified pipeline for STT → LLM → TTS. Mix providers in a single call.

MCP Agent Governance

Give AI agents controlled access to tools with default-deny permissions, audit trails, and cost limits.

Data & Compliance

PII detection, data residency controls, and compliance reporting for regulated industries.

Who Uses GateFlow?

• Startups moving fast who don't want to build AI infrastructure
• Enterprises needing compliance, audit trails, and cost controls
• AI Teams managing multiple providers and models
• Agencies building AI products for clients with different requirements

Getting Started

Ready to try GateFlow?

1. Quickstart Guide - Make your first API call in 5 minutes
2. Core Concepts - Understand providers, routing, and caching
3. Architecture - How GateFlow works under the hood

Comparison

Feature	Direct Provider API	GateFlow
Multi-provider support	Manual integration each	Single API
Automatic fallbacks	Build yourself	Built-in
Semantic caching	Build yourself	Built-in
Cost tracking	Per-provider dashboards	Unified analytics
Model deprecation handling	Manual migration	Automatic fallbacks
Compliance reporting	N/A	HIPAA, GDPR, EU AI Act