Product

AI Agents for ERP

Implement governed AI agents and generative AI workflows around SyteLine and CloudSuite Industrial to solve real business problems.

AI agent example

Ask an ERP question in plain English, then review the evidence.

A governed agent should answer from approved ERP context, show the work behind the answer, and stop at human-reviewed actions such as buyer follow-up or exception assignment.

ERP Operations Agent governed workspace
human-reviewed actions
show me my late POs

I found 4 late purchase orders. Two are tied to production demand this week, and one needs buyer review because the promised date is missing.

POItem AreaDueDays LateNext Step
PO-10482raw materialMay 286buyer follow-up
PO-10511purchased partMay 304confirm promise date
PO-10534service itemJun 012low risk
PO-10567packagingJun 021watch list
Draft supplier follow-up Assign buyer review Export evidence

Perspective

AI should solve a business workflow, not sit beside ERP as a chatbot

Manufacturers do not need another generic AI demo. They need practical agents and generative AI workflows that understand the operating problem: invoices waiting for review, orders that need context, planning exceptions, support tickets without enough detail, reports that require manual explanation, or managers who need a reliable summary before making a decision.

The useful work starts by mapping the workflow, the ERP records involved, the people responsible for review, and the decision that should improve. From there, an AI agent can classify work, gather missing context, draft a summary, compare evidence, recommend the next step, or prepare an update for a human to approve.

We keep the implementation controlled. Agents should work from approved data sources, explain what they used, avoid exposing sensitive information, and stop before risky system updates unless the workflow has explicit approval rules. The point is measurable operating improvement, not AI experimentation for its own sake.

How we help

We design and implement AI agents, ERP copilots, and generative AI workflow tools that help teams reduce manual review, improve decisions, and move work through SyteLine or CloudSuite Industrial with clearer context.

AI agent implementation

Build agents that classify work, gather ERP context, draft responses, summarize exceptions, and prepare human-reviewed actions.

Generative AI workflows

Use GenAI to write, summarize, analyze, translate, and explain operational information inside a controlled business process.

ROI-focused automation

Start with measurable problems such as fewer manual touches, faster review cycles, better visibility, lower rework, or faster support response.

Where AI agents fit around ERP

AI is a good fit when the business process has repeated decisions, structured ERP evidence, and human reviewers who need better context before acting.

AP and document workflows

Extract invoice or document details, match them to ERP context, flag exceptions, and prepare review notes before posting or approval.

Order and customer service workflows

Summarize customer/order history, identify missing information, draft follow-up notes, and help users move exceptions to the right owner.

Planning and operations exceptions

Review shortages, late supply, demand changes, quality issues, production constraints, and other signals that slow daily decisions.

Support and knowledge workflows

Turn emails, Slack messages, screenshots, logs, and ERP details into a clear support brief with likely area, impact, evidence, and next questions.

Reporting and executive summaries

Convert reports, dashboards, and operational notes into plain-language summaries that explain what changed, why it matters, and what needs attention.

Process discovery and improvement

Review repeated manual steps and error patterns so the business can decide where automation, CloudConnect, reporting, or process redesign will produce ROI.

AI agent implementation approach

  1. Choose a business problem with a measurable baseline: time spent, touches per transaction, error rate, backlog, response time, or missed exceptions.
  2. Map the ERP records, documents, messages, reports, integrations, and human approvals involved in the workflow.
  3. Define the agent role, allowed data, prompts, tools, handoffs, escalation rules, and actions that require human approval.
  4. Build a pilot against real examples and compare the agent output to how experienced users handle the same work.
  5. Measure ROI, capture reviewer corrections, tighten controls, and expand only when the workflow is reliable enough to support production use.

Typical work

AI agentsERP copilotsGenAI workflowsException reviewDocument automationSupport triageROI tracking

Next step

Talk through where this fits in your environment.

Contact Business Intuition