Build AI Agents on Cleon1
- No credit card required
- 5-minute setup
- SOC 2 Type II certified
Build AI Agents on top of Cleon1
Build intelligent AI Agents on top of Cleon1, with Peliqan’s AI data foundation:
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- Cleon1 MCP Server – let Claude, ChatGPT, or any AI client query and update your Cleon1 data
- Cleon1 in n8n AI Agents – build automated workflows that reason on your data
- Cleon1 in Make – trigger AI-powered actions from your Cleon1 events
- Text-to-SQL on Cleon1 – ask questions in plain English, get SQL-powered answers
- Cleon1 RAG – semantic search with out-of-the-box embeddings (vectors)
- Cleon1 Graph RAG – traverse relationships across your data entities
- Unified 360° data – combine Cleon1 with 250+ other sources in one warehouse
Cleon1 MCP Server
Publish a Cleon1 MCP Server with full read and write capabilities.
Peliqan syncs a read-only copy of your Cleon1 data into its built-in warehouse – your AI agents query the cache, your live Cleon1 is never touched. Connect Claude, ChatGPT, or any MCP client and start querying Cleon1 in plain English.
Cleon1 in n8n
Build AI Chatbots and AI Agents in n8n that query your Cleon1 data using Text-to-SQL and perform RAG on Cleon1 documents and records.
Peliqan acts as the data layer – syncing your Cleon1 data, converting natural language to SQL, and returning results your n8n agent can act on.
Implement a “Text to SQL” chatbot on Cleon1
Implement an AI Chatbot that answers analytical questions on Cleon1 data using Text-to-SQL.
Ask “what were my top 10 customers last quarter?” or “which deals are stalled?” and get instant, accurate answers.
Peliqan converts your question to SQL, runs it against your Cleon1 warehouse, and returns structured results – no SQL knowledge required.
Implement a chatbot with RAG on Cleon1
Implement RAG (retrieval-augmented generation) on Cleon1 data with Peliqan’s out-of-the-box vector store.
Peliqan automatically creates embeddings of your Cleon1 records, notes, and documents – so your AI agents can search semantically, not just by keywords.
Combine RAG with Text-to-SQL for AI that can both reason on numbers and understand context.
Combine Cleon1 data with 250+ sources
Combine data from Cleon1 with 250+ other connectors in Peliqan’s built-in warehouse.
Build unified 360° views of customers, deals, products, or employees – pulling from Cleon1, your CRM, ERP, HR systems, and more.
Feed these unified data models to your AI Agents so they can answer cross-functional questions in a single query.
Prepare your Cleon1 data for AI
Access, combine, and report on data from Cleon1 and all your SaaS apps instantly. Gain valuable insights by bringing all your business data together in one place within minutes.
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.
Frequently Asked Questions
Why do I need Peliqan for my AI ?
Most AI tools can’t access your Cleon1 data directly. Peliqan solves this by syncing Cleon1 into a built-in data warehouse and exposing it through MCP, Text-to-SQL, and RAG.
Your AI agents get governed, real-time access to Cleon1 data combined with 250+ other sources – without building custom integrations.
Peliqan is the only platform that lets AI agents combine structured SQL queries with semantic RAG search on Cleon1 data in a single context.
How to build an AI agent for Cleon1 ?
There are different ways to build an AI agent that can query data in Cleon1 and take actions in Cleon1. For example you can build an AI agent in n8n and use Peliqan as the data foundation. Peliqan will sync your Cleon1 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 Cleon1 data, combined with data from 250+ other sources.
How can I use Cleon1 in n8n ?
First sign up for a free trial on Peliqan.io, next connect Cleon1 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 Cleon1 data using Text to SQL.
How to use RAG with Cleon1 ?
There are different options to use RAG (retrieval augmented generation) in your AI Agent with Cleon1 data. One option is to create a workflow in n8n that fetches all Cleon1 data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.
How to build an MCP Server for Cleon1 ?
Connect Cleon1 in Peliqan, then create an API handler using the built-in MCP template. Expose the Cleon1 tables and actions your AI needs, set role-based permissions, and run pip install mcp-server-peliqan to connect Claude or ChatGPT. Your AI agents query a cached copy of your data – your live Cleon1 is never touched. The full setup takes under 10 minutes.
How do I build an AI chatbot with “Text to SQL” for Cleon1 ?
n8n is a great tool to build AI chatbots that use Text to SQL, to answer any analytical question on your Cleon1 data. Any question will be converted by the AI agent into an SQL query, which is executed by Peliqan on the Cleon1 data in the data warehouse.
How to create embeddings in a vector store for Cleon1 data ?
In order to prepare your Cleon1 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 Cleon1 data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.
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