Most large language models (LLMs) are trained for one-on-one interactions. You ask a question, it gives you an answer. But real enterprise software doesn’t work like that. It’s collaborative — multiple people working on a ticket, reviewing a report, managing a client file. And when it comes to AI, that’s where things fall apart.
AI doesn’t inherently track “who said what,” which version of the file was edited, or when approvals were given. Without robust session control and shared context handling, the AI can’t maintain a reliable thread — and collaborative enterprise tools start producing inconsistent, or even dangerous, outcomes.
If you’re building an AI-powered feature inside a CRM, ERP, project management tool, or support dashboard, chances are:
LLMs aren’t designed to interpret or retain multi-user state natively. They only “see” what’s passed in the current prompt. That’s why it’s critical to work with an AI app development agency or AI software platform agency that understands how to engineer AI for shared enterprise logic.
Build a persistent state layer that stores:
Dynamically adjust prompts depending on who is asking and what’s been done before.
“As the account manager, here’s what the analyst has flagged. What would you like to approve or escalate?”
An experienced AI software company will:
LLMs don’t understand collaboration — but your enterprise apps do. Without custom architecture, AI will always default to 1:1 mode, causing frustration or failure in multi-user workflows.
Working with an AI app development agency that’s already solved this at the enterprise level is the fastest path to multi-user AI that works.
Need help bridging AI with real-world collaboration? AndMine builds AI-powered platforms with session logic and context control — so your team stays aligned, and your AI stays useful.
