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Integrate Perplexity AI with your AI CRM

Perplexity AI provides conversational AI models for generating human-like text responses

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Explore Triggers and Actions

Create Async Chat Completion

Create Async Chat Completion (POST /v1/async/sonar). Submits an asynchronous chat completion request for long-running tasks. Returns immediately with a request ID that can be polled using the Get Async Chat Completion action. Only the 'sonar-deep-research' model is supported for async processing. Async jobs have a 7-day TTL. Deep research generates very long responses (10K-100K+ words) with exhaustive multi-source analysis. Use the idempotency_key to prevent duplicate submissions. Poll with Get Async Chat Completion using the returned request ID to retrieve results when status is COMPLETED.

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Create Chat Completion

Perplexity Sonar Chat Completions (POST /v1/sonar). Generates web-grounded conversational AI responses with citations. Supports multiple Sonar models optimized for different use cases: - sonar: Fast, cost-effective for simple queries - sonar-pro: Enhanced quality for complex questions - sonar-reasoning-pro: Chain-of-thought reasoning with <think> blocks - sonar-deep-research: Exhaustive multi-source research (generates very long responses, 10K+ words; prefer the async endpoint for this model) Features: web search grounding, citations, images, structured JSON output, search filtering by domain/date/language/recency, and streaming. Important constraints: - search_recency_filter and date filters (search_after_date_filter, search_before_date_filter, etc.) are mutually exclusive. Use one or the other, not both. - Messages with the 'tool' role must alternate with 'assistant' messages. A valid pattern is: system -> user -> assistant -> tool -> user. - The 'stop' parameter is not currently supported by the API.

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Create Contextualized Embeddings

Create Contextualized Embeddings (POST /v1/contextualizedembeddings). Generates document-aware embeddings where chunks from the same document share context. Unlike standard embeddings, these recognize sequential relationships within documents, improving retrieval quality. Models: pplx-embed-context-v1-0.6b (1024 dims) and pplx-embed-context-v1-4b (2560 dims). Both support Matryoshka dimension reduction and INT8/binary quantization.

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CreateEmbeddings

Generate vector embeddings for independent texts (queries, sentences, documents). This action takes one or more input texts and generates vector embeddings using Perplexity AI's embedding models. Embeddings are useful for semantic search, similarity matching, and machine learning downstream tasks. Supported models: - pplx-embed-v1-0.6b: Smaller, faster model (1024 dimensions) - pplx-embed-v1-4b: Larger, more accurate model (2560 dimensions) The output embeddings are base64-encoded for efficient transmission. Use the dimensions parameter to reduce embedding size for faster processing when full precision is not required (Matryoshka representation).

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Execute Agent

Create Agent Response (POST /v1/agent). Orchestrates multi-step agentic workflows with built-in tools (web search, URL fetching, function calling), reasoning, and multi-model support. Streaming is not supported by this action. At least one of 'model', 'models', or 'preset' must be provided. Available presets: 'fast-search', 'pro-search', 'deep-research'. The 'deep-research' preset generates very long responses (10K-100K+ words) with exhaustive multi-source analysis. Available models include Perplexity Sonar, OpenAI, Anthropic, Google, xAI, and NVIDIA models at direct provider rates. Use the List Models action to see available model identifiers.

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Get Async Chat Completion

Get Async Chat Completion (GET /v1/async/sonar/{id}). Retrieves the result of an asynchronous chat completion request by its ID. Use this to poll for the result after creating an async job. The response includes the status and, when completed, the full completion.

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List Async Chat Completions

List Async Chat Completions (GET /v1/async/sonar). Retrieves a list of all asynchronous chat completion requests for the authenticated user. Use this to see the status of all your pending, completed, and failed async jobs.

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List Models

List Models (GET /v1/models). Lists models available for the Agent API. Returns model identifiers that can be used with the Agent endpoint. The response follows the OpenAI List Models format for compatibility. This is a public endpoint that does not require authentication.

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Perplexity Search (Raw Results)

Search the Web (POST /search). Returns raw, ranked web search results directly from Perplexity's index without LLM processing. Faster and cheaper than chat completions when you need raw results. Supports filtering by domain, date, language, country, and recency. Max 20 results per request. Important: search_recency_filter and date filters (search_after_date_filter, search_before_date_filter, last_updated_after_filter, last_updated_before_filter) are mutually exclusive. Use one or the other, not both.

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How the Perplexity AI integration works

The Perplexity AI integration connects your Dench AI CRM directly to Perplexity AI, so agents can read and act on your Perplexity AI data as part of everyday work — answering questions in chat, keeping your CRM in sync, and running automations without anyone copying data between tools.

9 actions are available for agents to invoke on your behalf. Every call runs through Perplexity AI's own authorization, scoped to the account you connect.

Set up Perplexity AI in Dench

  1. 1

    Sign in to your Dench workspace and open Integrations.

  2. 2

    Find Perplexity AI and click Connect — you'll authorize access through Perplexity AI's own sign-in flow. No API keys or code required.

  3. 3

    Ask an agent to use Perplexity AI in chat, or call it from an automation.

  4. 4

    Manage or disconnect the connection any time from workspace settings.

Frequently asked questions

How does the Perplexity AI integration work with Dench?

The Dench Perplexity AI integration connects your AI CRM to Perplexity AI, so AI agents can work with your Perplexity AI data as part of chats, automations, and CRM workflows. You connect your account once, and every agent in your workspace can use it — governed by your workspace permissions.

What actions can AI agents perform with Perplexity AI via Dench?

The Perplexity AI integration currently exposes 9 actions, including Create Async Chat Completion, Create Chat Completion, Create Contextualized Embeddings, CreateEmbeddings, Execute Agent, and Get Async Chat Completion. Agents invoke them on your behalf from chat or from automations.

Do I need to write code to connect Perplexity AI to Dench?

No. You connect Perplexity AI from your Dench workspace using Perplexity AI's own sign-in and authorization flow — no API keys to copy, no glue code to maintain.

Is the Perplexity AI integration secure?

Connections are authorized through Perplexity AI's own authentication flow, and Dench stores only the authorization needed to act on your behalf. You can review and disconnect the Perplexity AI connection from your workspace settings at any time.