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Build AI Agents on Emprova

Build intelligent AI Agents on top of Emprova with Peliqan, the leading data foundation for the Agentic AI world.

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Emprova

Build AI Agents

Build AI Agents on top of Emprova

Build intelligent AI Agents on top of Emprova, with Peliqan’s AI data foundation:

  • Emprova MCP Server
  • Emprova in n8n AI Agents
  • Emprova in Make
  • “Text to SQL” on Emprova data
  • Emprova RAG with out-of-the-box embeddings (vectors)
  • Emprova Graph RAG
  • Query unified 360° data combining Emprova and other data

Emprova MCP Server

Publish a Emprova MCP Server to query data from Emprova and to take actions in Emprova such as doing updates and adding new data in Emprova.

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Build MCP Server

Build AI agents in n8n

Emprova in n8n

Build AI Chatbots and AI Agents in n8n that can perform “Text to SQL” to query Emprova data and perform RAG and Graph RAG on information from Emprova.

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Implement a “Text to SQL” chatbot on Emprova

Implement an AI Chatbot that can answer analytical data questions on Emprova data using “Text to SQL”. 

Text to SQL

Implement a chatbot

Implement a chatbot with RAG on Emprova

Implement RAG (retrieval-augmented generation) on Emprova data with an out-of-the-box vector store (embeddings) of all business entities and other information in Emprova.

Combine Emprova data with 250+ sources

Combine data from Emprova with data from 250+ other connectors, and build 360° views of business entities such as customers, leads, products, employees etc.

Feed unified 360° data models to your AI Agents with RAG and “Text to SQL”. Allow your AI Agents to access all business data in one uniform data model.

Combine data

Prepare your Emprova data for AI

Access, combine, and report on data from Emprova and all your SaaS apps instantly. Gain valuable insights by bringing all your business data together in one place within minutes.

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SaaS Data Cockpit

Unify, Automate & Activate Your Data 

Connect all your SaaS apps, databases, and spreadsheets into one workspace. Build automations, analytics pipelines, and data apps — all in one place.

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Frequently Asked Questions

Why do I need Peliqan for my AI ?

Peliqan is an all-in-one data platform with 250+ data connectors (ERP, CRM, Accounting, ATS/HRM, cloud storage etc.) – including Emprova – and a built-in data warehouse. Peliqan allows you to unleash, prepare and combine your Emprova data for AI, including relational & non-relational data. Peliqan turns your Emprova data into 360° views that can be used in AI Agents built in n8n, Make, langChain, langGraph or any other framework. Use Peliqan to create embeddings, store them in a vector store so that your AI chatbots can use RAG and Graph RAG, combined with Text-to-SQL for analytical reasoning. Peliqan is the only platform that allows your AI Agents to combine RAG and Text-to-SQL to apply deep reasoning on your Emprova data. Use Peliqan to expose any Emprova as an MCP server to query data and to take actions.

There are different ways to build an AI agent that can query data in Emprova and take actions in Emprova. For example you can build an AI agent in n8n and use Peliqan as the data foundation. Peliqan will sync your Emprova data to its built-in data warehouse and allow the AI Agent to perform “Text to SQL” and RAG to answer questions and to perform reasoning on Emprova data, combined with data from 250+ other sources.

First sign up for a free trial on Peliqan.io, next connect Emprova in Peliqan. Once that is done, create an AI agent in n8n and use the Peliqan n8n node in your worflow. Add Peliqan as a “tool” to your AI Agent node, so that the AI agent can query your Emprova data using Text to SQL.

There are different options to use RAG (retrieval augmented generation) in your AI Agent with Emprova data. One option is to create a workflow in n8n that fetches all Emprova data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.

In Peliqan, you can set up API endpoints and expose them as MCP Server. In the API endpoint handler script, you can configure actions to be taken in Emprova such as querying data, doing lookups, adding new items or performing updates.

n8n is a great tool to build AI chatbots that use Text to SQL, to answer any analytical question on your Emprova data. Any question will be converted by the AI agent into an SQL query, which is executed by Peliqan on the Emprova data in the data warehouse.

In order to prepare your Emprova data for RAG, you need to create embeddings and store them in a vector store. This can be done by creating a workflow in n8n that fetches all Emprova data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.

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Built-in data warehouse, superior data activation capabilities, and AI-powered development assistance.

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