Unified model API
Access more than 600 AI models through one API signature rather than maintaining separate integrations for each provider.
each::labs
Freemium
each::labs provides a single API for orchestrating more than 600 AI models, with routing, fallback handling, observability, and usage-based pricing. It is designed for teams building and operating production AI applications across video, image, audio, and text workflows.
What is each::labs?
each::labs is an AI orchestration platform that puts more than 600 models behind one API. It is intended for teams that want to build production AI applications without implementing separate model connections and operational handling for every provider. Supported model workflows shown on the site include text, image, video, and audio-related tasks.
The platform combines model access with routing and operational tooling. It can retry failed calls, automatically fall back to another provider, and route traffic when a provider’s latency degrades. Its observability features include production traces, error-rate monitoring, per-user cost tracking, and model comparison or workflow tools described by customer stories.
Pricing is pay per call, with provider pricing passed through without an inference markup. The pricing page also states that 10,000 traces and 5 GB of storage are included, while model costs vary by provider, model, modality, inputs, resolution, duration, tokens, or other usage factors. The service states that it does not train on customer traffic.
What can each::labs do?
Routing and fallback
Route requests across providers and automatically retry or move to another provider when a model fails or its latency exceeds a configured threshold.
Observability and cost tracking
Monitor production traces, error rates, and per-user costs so teams can investigate reliability and understand usage.
Model comparison and workflows
Compare models and use workflow templates to test outputs, identify suitable models, and assemble AI production processes.
Multi-modal model catalog
Browse model calls for image, video, audio, and text tasks, including text-to-image, image-to-video, text-to-video, reference-to-video, video editing, and speech-to-text examples.
Pass-through inference pricing
Pay the upstream provider’s listed inference price without an additional inference markup; the final cost can depend on inputs and model-specific usage rules.
Use Cases
“Production AI applications”
Teams can use one model interface while operating applications that depend on multiple providers, reducing the need to build and maintain each provider connection separately.
“AI creative production”
Product teams working with advertising or other creative workflows can evaluate image and video models, use reference-based generation, and compare results before selecting a model.
“Video generation and processing”
Developers can build workflows around text-to-video, image-to-video, reference-to-video, video editing, and related generated-video tasks through the platform’s video model catalog and Video API.
“Reliability-sensitive model calls”
Applications affected by provider outages or changing latency can use retries, fallback routing, and latency-based traffic shifting to keep requests moving when a provider degrades.
“Usage and model evaluation”
Engineering and product teams can inspect traces, compare model behavior, and track costs by user while deciding which provider or model best fits an application.
Frequently Asked Questions
What is each::labs?
It is an AI orchestration platform that provides access to more than 600 models through one API, with routing, fallback, observability, and usage-based inference pricing.
Which AI modalities are available?
The pricing catalog is organized around video, image, audio, and text. Examples on the site include text-to-image, image editing, text-to-video, image-to-video, reference-to-video, video editing, and speech-to-text.
How is inference priced?
The pricing page says customers pay the provider’s price with no additional inference markup. Costs vary by model and by usage inputs such as resolution, duration, tokens, output, or credits. The platform also states that there are no bandwidth fees, seat licenses, or contracts on the pricing page.
What happens when a model or provider fails?
The platform describes retries and automatic fallback to another provider. It also describes shifting traffic when a provider’s latency exceeds a configured threshold.
Does each::labs train on customer traffic?
The product’s home-page description states that it does not train on customer traffic.
Quick Facts
- Category
- Developer Tool
- Platform type
- AI model orchestration API
- Model coverage
- 600+ models
- Modalities
- Video, image, audio, and text
- Pricing model
- Pay per call at provider rates; no inference markup
- Source domain
- eachlabs.ai
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