AI in JAMS
AI for job scheduling and workflow automation
JAX and JAMS MCP bring AI to your automation without asking you to hand over your data. Choose the model JAX runs on, including a local model that keeps everything inside your own network, at no extra cost.
One customer moved from Appworx to JAMS in 26 days.
See JAX and JAMS MCP running on a live JAMS environment.
The gap
Automation outgrew the team watching it
Jobs keep multiplying across SQL Server, ADF, Airflow, SAP, JDE, and Banner. Automation knowledge concentrates in one or two people, and a 2 a.m. failure means digging across systems before anyone reaches root cause. Leadership wants an AI strategy, but most AI options mean sending operational data outside your control. JAMS closes both gaps at once.
Nothing to trust, because nothing has to leave
Most AI features ask you to trust a vendor with your data. JAX removes the question: choose a local model, run it entirely inside your own network, and there is no external AI in the picture at all. Choose a commercial provider instead if you prefer; JAMS never trains on your data, either way. JAMS MCP uses whichever model your AI coding tool already runs.
Works with any LLM
Two ways to run automation in plain language
The AI lives in the product, not in the support queue. Same control model, different entry point.
JAX: ask JAMS anything
An AI agent built into the JAMS Web Client. Find jobs, troubleshoot failures, and get how-to answers, grounded in real JAMS documentation.
JAMS MCP: stay in your tools
A connector that brings JAMS into Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Query jobs and manage runs without leaving your tool.
The control model behind every action
The list of things AI can do will grow. These four rules will not.
Identity
Every action runs as the signed-in user, with that user's exact permissions. There is no elevated AI account, ever.
Approval
Reads flow freely. Writes wait for your confirmation, whether the request comes from JAX or from your AI coding tool.
Model and data
Neither feature hosts a model. For JAX, bring a commercial provider or a local model on your own hardware. For JAMS MCP, the model belongs to whichever AI coding tool you're already using. JAMS never trains on your data, either way.
Logging and audit
Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change.
See the control model in action
Watch a short demo of JAX and JAMS MCP handling a real job failure, live.
Built for the people who get paged at 2 a.m.
Tool-native engineers
DevOps, platform, SRE, and integration developers who live in Cursor, Copilot, or Claude. JAMS MCP meets them there, with nothing new to stand up.
In-product IT ops
IT ops, batch teams, support, and NOC staff who want a fast, trustworthy answer without opening an AI coding tool. JAX meets them inside JAMS.
IT leaders and buyers
Directors and CIOs who own the AI decision and its risk. They get control of the model, the data, and what the AI can do, at no extra cost.
Common questions, direct answers
Do we have to send data to OpenAI or Anthropic?
Can the AI delete or change our jobs?
Will it exceed a user's permissions?
Does it learn from our data?
What does it cost?
Is everything logged?
