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Enterprise Layer Intelligence
Categories/AI Orchestration & MLOps/each::labs
each::labs

each::labs

Founded 2023

Connect to hundreds of generative AI models through a single unified interface

Pricing model

Demo

You can use Eachlabs to route requests across more than six hundred artificial intelligence models through a single application programming interface. It connects to multiple providers for video, image, audio, text, and 3D generation without needing individual software development kits. When a provider fails or experiences slow response times, the system redirects traffic to backup models in less than one hundred twenty milliseconds. You can also monitor performance metrics, compare output quality, build multi-model pipelines, and track usage expenses for individual end users across all connected services.

What each::labs does

Route API requests to alternative models when primary providers failGenerate video clips using start and end frame referencesTrack AI inference expenses per customer for billing purposesInspect production logs and execution traces across all model callsSwitch between model versions without rewriting client integration codeChain multiple generative models together inside single workflowsTest and benchmark output quality across competing AI providersUnified access to over 600 generative AI models across video, image, text, and audioAutomatic failover routing to backup providers in under 120 milliseconds during outagesPay-as-you-go pricing matching upstream provider inference rates with zero markupMulti-model workflow chaining to combine outputs from different AI providersLive observability and request tracing to monitor error rates and latencyPer-user cost tracking to measure inference expenses by customer accountPrompt refinement and style controls for image and video creation models

Pricing breakdown

Pricing model: Book a demo

Frequently asked

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Eachlabs, AI orchestration, model routing, generative AI, AI API, LLM gateway, video generation, image generation, model failover, AI observability, multi-model workflows, Kling, MiniMax, Gemini, AI infrastructure