Build AI Agents on IMAP
Build intelligent AI Agents on top of IMAP with Peliqan. Query your data in plain English, automate workflows with AI, and write changes back – all through a single platform with 300+ connectors and a built-in data warehouse.
- No credit card required
- 5-minute setup
- SOC 2 Type II certified
Build AI Agents on top of IMAP
Build intelligent AI Agents on top of IMAP, with Peliqan’s AI data foundation:
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- IMAP MCP Server – let Claude, ChatGPT, or any AI client query and update your IMAP data
- IMAP in n8n AI Agents – build automated workflows that reason on your data
- IMAP in Make – trigger AI-powered actions from your IMAP events
- Text-to-SQL on IMAP – ask questions in plain English, get SQL-powered answers
- IMAP RAG – semantic search with out-of-the-box embeddings (vectors)
- IMAP Graph RAG – traverse relationships across your data entities
- Unified 360° data – combine IMAP with 250+ other sources in one warehouse
IMAP MCP Server
Publish a IMAP MCP Server with full read and write capabilities.
Peliqan syncs a read-only copy of your IMAP data into its built-in warehouse – your AI agents query the cache, your live IMAP is never touched. Connect Claude, ChatGPT, or any MCP client and start querying IMAP in plain English.
IMAP in n8n
Build AI Chatbots and AI Agents in n8n that query your IMAP data using Text-to-SQL and perform RAG on IMAP documents and records.
Peliqan acts as the data layer – syncing your IMAP data, converting natural language to SQL, and returning results your n8n agent can act on.
Implement a “Text to SQL” chatbot on IMAP
Implement an AI Chatbot that answers analytical questions on IMAP 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 IMAP warehouse, and returns structured results – no SQL knowledge required.
Implement a chatbot with RAG on IMAP
Implement RAG (retrieval-augmented generation) on IMAP data with Peliqan’s out-of-the-box vector store.
Peliqan automatically creates embeddings of your IMAP 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 IMAP data with 300+ sources
Combine data from IMAP with 300+ other connectors in Peliqan’s built-in warehouse.
Build unified 360° views of customers, deals, products, or employees – pulling from IMAP, 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 IMAP data for AI
Access, combine, and report on data from IMAP 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 IMAP data directly. Peliqan solves this by syncing IMAP 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 IMAP 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 IMAP data in a single context.
How to build an AI agent for IMAP ?
There are different ways to build an AI agent that can query data in IMAP and take actions in IMAP. For example you can build an AI agent in n8n and use Peliqan as the data foundation. Peliqan will sync your IMAP 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 IMAP data, combined with data from 250+ other sources.
How can I use IMAP in n8n ?
First sign up for a free trial on Peliqan.io, next connect IMAP 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 IMAP data using Text to SQL.
How to use RAG with IMAP ?
There are different options to use RAG (retrieval augmented generation) in your AI Agent with IMAP data. One option is to create a workflow in n8n that fetches all IMAP 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 IMAP ?
Connect IMAP in Peliqan, then create an API handler using the built-in MCP template. Expose the IMAP 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 IMAP is never touched. The full setup takes under 10 minutes.
How do I build an AI chatbot with “Text to SQL” for IMAP ?
n8n is a great tool to build AI chatbots that use Text to SQL, to answer any analytical question on your IMAP data. Any question will be converted by the AI agent into an SQL query, which is executed by Peliqan on the IMAP data in the data warehouse.
How to create embeddings in a vector store for IMAP data ?
In order to prepare your IMAP 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 IMAP data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.
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