#Agentic Ai
Guides on agentic AI — systems where AI agents plan, decide, and act across multi-step workflows in production business environments.
6 resources
AI Agent Production Deployment: What We Learned Shipping 3 Enterprise Agents
We have shipped 3 production AI agents — a contact centre quality monitor (scaled 50 to 80+ agents), a CRM lead scorer, and a manufacturing cost estimator. Here's what each cost, how long it took, and what surprised us.
AI Agent Platform Comparison 2026: Build vs Buy for Enterprise
AI agent platforms range from $50/month no-code tools to $200,000 custom builds. Here's how CrewAI, AutoGen, LangGraph, and custom development compare for enterprise production use in 2026.
What Is Model Context Protocol (MCP)? A Business Guide
Model Context Protocol (MCP) is an open standard that lets AI systems connect to business tools through one interface instead of custom integrations. Here's what it means for enterprise AI costs, timelines, and architecture decisions.
AI Agent vs RPA vs Workflow Automation: What Actually Works in 2026
RPA automates repetitive screen actions — clicking buttons, copying data between systems, filling forms. Workflow automation enforces business rules — if X happens, do Y. AI agents make decisions with incomplete information — reading documents, classifying intent, choosing next steps. Most enterprises need all three, but waste money applying the wrong tool to the wrong problem. This guide explains when each technology works, what it costs, and where the boundaries are.
What Is AI Model Routing? How Production Systems Use Tiered Models to Cut API Costs
AI model routing directs different tasks to different model tiers based on complexity — classification to cheap models, reasoning to expensive ones. It reduces API costs by 80–95% in production systems. Most development teams skip it because it requires more upfront architecture work.
Custom Enterprise AI Chatbot: What It Includes, When to Build vs Buy (2026)
An enterprise AI chatbot handles employee queries, customer support requests, or sales qualification by retrieving answers from internal knowledge bases, CRM records, documentation, and structured data — rather than generating generic responses. The difference between a custom enterprise chatbot and an off-the-shelf deployment is the quality of the retrieval layer and the depth of system integration.