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Intelligent AI agent platform that automates business workflows using LLM-powered agents, tool calling, task orchestration, and contextual decision-making. Designed to connect business processes, APIs, and data sources while reducing repetitive work and enabling reliable AI-assisted operations.
@mahmoud wael How are you handling retries and audit trails when tool calls fail mid-orchestration? Contextual decision-making gets much more useful when operators can inspect each step.
I handle this by treating each tool call as a traceable execution step. Failed calls are captured with the tool name, input, error, retry status, and execution context, while the workflow can retry or fall back based on the failure type. I also keep an audit trail for each step...
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I’m currently building a RAG system for an e-commerce company, basically giving an AI assistant access to the company’s own knowledge and product information so it can give useful, context-aware responses instead of just generating random answers.
The interesting part isn’t just connecting an LLM.
It’s making sure the AI can:
→ Find the right information
→ Understand the user’s question
→ Retrieve relevant context
→ Give an accurate response
→ Actually be useful in a real business workflow
Still working on it, but I’m excited about where it’s going.
This is the kind of AI automation I enjoy building, systems that solve actual business problems, not just AI demos.
Building something similar? Let’s talk.
One thing that will save you a lot of time: build a small evaluation set early — 50–100 real questions with the document or product that should be retrieved for each. Before tuning prompts, measure retrieval quality (does the right doc surface in the top 3?) with it. Chunk size...
People don’t like to wait for your customer support system.
It shows that you don’t care enough for your users.
Introducing Assistia, a template for AI customer service automation platforms.
Designed specifically for SaaS companies.
It’ll reduce response times and cut support costs by up to 70%.
With its visual storytelling and social proof sections, strategic CTAs, and mobile-first design,
You can launch your website fast.
Check the comments for the links.
This is my AI Customer Support and Lead Generation Agent, built with n8n.
The workflow starts when a customer sends a message. The AI Agent understands the customer's request and responds automatically.
It also uses conversation memory to maintain context during the conversation.
When a customer wants to place an order, the agent collects important details such as their name, phone number, email, service, quantity, and requirements.
Finally, the customer's information is automatically saved into Google Sheets as a new lead.
This automation helps businesses handle customer inquiries and organize leads without manual work.
Agents are amazing. Building & using them is a genuine wise career choice in my opinion.
