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AI/ML2025

Facilis - Agentic AI Tools

Building production agentic tools for industrial enterprise customers using MCPs, Node, React, and TypeScript.

Role
AI Engineer
Timeline
Apr 2025 - Present
Team
Facilis Engineering
Year
2025
Facilis

Overview

Building agentic tools and AI systems for industrial enterprise customers at Facilis. Working with cutting-edge technologies including Model Context Protocol (MCP), creating intelligent agents that can understand context, make decisions, and interact with complex enterprise systems.

The Challenge

Industrial enterprises need AI systems that can understand complex workflows, integrate with existing infrastructure, and make intelligent decisions in real-time. Traditional automation falls short when dealing with the nuanced requirements of industrial operations.

The Solution

Developing sophisticated agentic systems using MCPs that enable AI to maintain context across interactions, reason about complex scenarios, and take autonomous actions within defined parameters. Built using modern stack (Node.js, React, TypeScript) to ensure scalability and maintainability.

Impact & Results

Deployed AI agents serving industrial enterprise customers

Implemented Model Context Protocol for intelligent agent systems

Built production-grade tools with React and TypeScript

Enabled autonomous decision-making in enterprise workflows

Technologies

MCPNode.jsReactTypeScriptAI AgentsEnterprise SystemsREST APIs

Project Links

Tags

MCPNode.jsReactTypeScriptAgentsEnterprise AI
Zakaria Kortam | AI Engineer & Product Engineer