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