Unify

Consolidates access to 100+ language models from different providers (OpenAI, Anthropic, Google, etc.) through a single standardized API endpoint. Eliminates the need to manage separate API keys, authentication, and integration code for each provider.

Automatically selects the optimal language model for each request based on real-time metrics including cost, latency, and quality. Routes requests dynamically without requiring code changes when preferences shift.

Caches responses and deduplicates identical or similar requests to reduce redundant API calls and associated costs.

Centralizes management of API keys and credentials for all connected providers. Eliminates the need to distribute and manage multiple provider keys across applications.

Distributes requests across multiple providers and models to balance load, prevent rate limiting, and optimize resource utilization.

Runs comparative benchmarks across models to measure quality, speed, and cost for specific use cases. Provides data-driven insights for model selection.

Implements automatic failover to alternative models when the primary model fails or is unavailable. Ensures request completion without requiring application-level error handling or code changes.

Tracks and measures latency, cost, and quality metrics for each model and request in real-time. Provides continuous visibility into how different models perform across various dimensions.

Provides granular cost analysis showing spending by model, provider, endpoint, and time period. Enables detailed cost attribution and ROI justification to stakeholders.

Provides visibility into capabilities, pricing, latency, and quality characteristics across 100+ models from different providers. Enables informed decision-making about which models to use.

Optimizes request batching across multiple models to reduce costs and improve throughput. Groups requests intelligently to maximize efficiency.

Automatically translates requests into the correct format for each provider's API, handling differences in parameter names, request structures, and response formats.

Allows teams to define custom routing rules based on business logic, request characteristics, or custom metrics. Enables fine-grained control over which model handles which request.

Enforces usage limits and quotas across models and providers to prevent unexpected costs and maintain budget control. Tracks consumption against defined limits.