Cohere API

Command R+ model generates coherent text and multi-turn conversational responses across 23 languages using a transformer-based architecture optimized for enterprise reasoning tasks. The model integrates with RAG systems to ground generation in retrieved documents, enabling fact-anchored outputs that cite source data. Supports streaming responses for real-time user interaction and handles complex reasoning chains for multi-step problem solving.

Embed 4 model converts text into fixed-dimensional vector representations (embeddings) that capture semantic meaning across 100+ languages using a transformer-based encoder architecture. Embeddings enable semantic search, document clustering, and similarity comparisons without requiring explicit keyword matching. Available in Small and Medium tier variants for deployment flexibility, with support for both API-based and dedicated Model Vault instance deployment for data privacy.

North is an all-in-one AI platform built on Cohere's models that provides pre-built agents for routine tasks (data retrieval, document processing, customer support) and workflow automation capabilities. Agents are composed of generation, retrieval, and reasoning components with built-in guardrails and monitoring. Enables non-technical users to build AI workflows via UI without coding, while supporting advanced customization for developers.

Command R+ generative model supports 23 languages for text generation and conversation, enabling multilingual chatbots and content creation without language-specific model selection or switching. Language support is built into single model rather than requiring separate language-specific models.

Rerank models (3.5, 4 Fast, 4 Pro) re-score search results to optimize relevance ranking using learned-to-rank algorithms that consider semantic similarity, user context, and interaction history. Operates as a post-processing layer after initial retrieval (from BM25, vector search, or hybrid systems), dynamically adjusting result order based on user preferences and query intent. Available in multiple performance tiers (Fast for latency-sensitive, Pro for accuracy-focused) and deployment options (API or Model Vault).

Transcribe endpoint converts audio input to text across 14 languages using an ASR (automatic speech recognition) model optimized for real-world conversational environments (background noise, accents, informal speech). Integrates downstream with generative and retrieval systems to enable end-to-end speech-driven workflows (e.g., voice search, voice-to-chat). Handles streaming audio input for real-time transcription use cases.

Compass product provides pre-built connectors to enterprise data sources (Salesforce, Slack, Jira, Google Drive, etc.) that automatically index documents and enable retrieval-augmented generation without manual ETL. Connectors handle authentication, incremental syncing, and document chunking, feeding retrieved context directly into Command R+ for grounded text generation. Managed index handles vector storage and similarity search internally.

Fine-tuning capability allows customization of Command R+ or embedding models on enterprise-specific data to improve performance on domain-specific tasks (legal document analysis, medical coding, technical support). Training process uses supervised learning on labeled examples, updating model weights to specialize behavior. Supports both generative and embedding model fine-tuning with custom pricing based on data volume and training duration.

Model Vault provides dedicated, fully-managed deployment of Cohere models (Command R+, Embed 4, Rerank variants) in customer-controlled environments (VPC, on-premises, or Cohere-managed private cloud). Eliminates data sharing with Cohere infrastructure, enabling compliance with data residency regulations (GDPR, HIPAA, SOC 2). Pricing is hourly or monthly commitment-based rather than per-token, with fixed costs regardless of usage volume.

Two-tier authentication system provides trial API keys (auto-generated on account creation, rate-limited, free) for experimentation and production keys (requires application approval, pay-as-you-go billing) for commercial use. Trial keys are explicitly prohibited for production/commercial workloads. Authentication uses standard API key headers (implementation details unknown) with rate limiting enforced per key tier.

Single API surface exposes multiple specialized models (Command R+ for generation, Embed 4 for embeddings, Rerank variants for ranking, Transcribe for speech) with consistent request/response patterns across endpoints. Enables building complex AI workflows (e.g., transcribe → generate → rerank) by chaining API calls without context switching between different provider APIs. Model selection is explicit via endpoint or model parameter.

Production API usage is billed on a pay-as-you-go model based on token consumption (per-token pricing structure unknown). Billing is metered per API call with costs aggregated across all endpoints (generation, embeddings, ranking, transcription). No upfront commitment required, enabling cost-proportional scaling. Trial tier is free but rate-limited and non-commercial.