Experiential Labs

Experiential Labs is an AI infrastructure platform that provides a unified gateway for accessing and managing AI models through a single API. Developers can connect hosted models, their own provider API keys, and self-hosted models without maintaining separate integrations for every provider.

The platform is designed to simplify model access, improve reliability through provider fallback, and make AI usage and costs easier to track. Teams can also evaluate alternative models against their existing workloads and use production traffic to help optimize routing or develop specialized models.

Key Features

• Unified AI API: Access multiple AI models through an OpenAI-compatible API, reducing the need to build separate integrations for different providers.
• Provider Routing and Fallback: Configure ordered provider routes so requests can fall back to another available route when a provider encounters capacity or transport errors.
• Bring Your Own Keys: Connect existing provider credentials and use them through the gateway.
• Usage and Cost Tracking: Attribute requests to customers or API keys and review usage and spending across workloads.
• Model Evaluation: Replay existing requests against alternative models and compare their responses before switching.
• Model Optimization: Use production traces to help develop specialized models and routing strategies tailored to specific tasks.
• Access and Budget Controls: Manage model access, API keys, and spending limits for different applications and workflows.

Typical Use Cases

• Multi-Model Application Development: Integrate multiple language models into a product through one consistent API endpoint.
• AI Infrastructure Management: Centralize model access and provider routing instead of maintaining separate integrations for each provider.
• AI Cost Optimization: Compare alternative models against real workloads to identify options that may reduce costs while maintaining output quality.
• Production Reliability: Configure fallback routes to reduce the impact of provider rate limits or temporary failures.
• Usage Attribution: Track model requests and costs by customer, application, or API key to better understand AI spending.

How It Works

1. Create an API key and configure the models or providers you want to use.
2. Point an OpenAI-compatible client to the Experiential Labs API endpoint.
3. Select a model and send requests through the unified gateway.
4. Configure routing, fallback, access controls, and usage attribution as needed.
5. Evaluate alternative models and use collected traces to explore further optimization.

Who It's For

Experiential Labs is designed for developers, AI startups, SaaS teams, and engineering organizations building applications powered by large language models. It is particularly relevant for teams that need to work with multiple model providers, manage inference costs, improve request reliability, or gain visibility into AI usage.

Experiential Labs brings model access, routing, evaluation, and usage management together to help teams operate AI-powered products through a unified infrastructure layer.