Beyond advice: agents that
actually do the work.
Book an AI Value WorkshopTake the free AI Readiness check
Not a chatbot. Something that
reasons, plans and executes.
Advice is where most AI consultancies stop. We keep going. This is where AI stops being a slide and starts being a result with custom agents built for your workflows and dropped into Teams and Microsoft Copilot, your governed ERP data hooked to Claude for dashboards you get in minutes, and process automation that collapses work that used to take days into hours. We don’t just advise on agents. We build and run them.
The word “agent” is overused, so here’s the honest version. A chatbot answers a question. An agent takes a goal, works out the steps, gathers what it needs across multiple systems, does the work, and hands you the result for approval. “Draft the sales order from this PO, match it to the customer’s contracted pricing, flag anything that doesn’t reconcile, and queue it for me to approve.” That’s not autocomplete, it’s usually a junior team member who never sleeps and always shows its working. The difference between the two is the difference between interesting and transformative.
Helping people reclaim their time
62
Percent of users recommend us to friends and family
2.5
Productivity gap between the most and least advanced AI adopters · McKinsey
30
faster expense-report preparation
MCP + Claude
Ask a question of your
ERP. Get a dashboard
back in minutes, not a
BI project.
Something that felt impossible eighteen months ago and is real today. Using the Model Context Protocol (MCP), we securely connect your governed ERP data to an assistant like Claude or Microsoft Copilot with your permissions intact and simply ask. “Show me AR ageing by entity with the top ten overdue accounts.” or “Chart cash position across the group for the last quarter.” Seconds later you have a live, cited dashboard you can act on or drop into a board pack.
What used to take a developer weeks to build at a cost, now becomes a conversation. The most exciting part is every query runs as the ERP user asking, bounded by what they’re permitted to see, every action logged which creates speed without the data-leak.
Build the agent once. Meet
people in the tools they already open.
The best agent in the world is useless if it is not used or needs another app to login to. Thus, we can help build agents that reaches your team in the surfaces they already use, like embedded in Acumatica, Sage Intacct or SAP, or via MCP through Microsoft Teams, Microsoft 365 Copilot, a web app, or Claude for example. In our agentic beta platform, we try to focus on building the agent once, with focus to deliver in on multiple surfaces – to drive adoption. And because the permission model travels with the agent, you can sleep easy at night knowing that these agents are controlled, and acts as the ERP user, with that user’s access.
- Finance Copilot (Answers questions over live ERP data, cited to source)
- Document Intake Agent (Reads PO PDFs or emails and drafts orders for approval)
- Approvals Agent (Routes, pre-checks and chases what’s stuck)
- Reconciliation Agent (Fans out across entities and reports the breaks)
Our own agents, already running in beta.
We can talk about this credibly because we’ve built it. Our own agentic platform (Levcore, in beta) runs the pattern end-to-end: permission-aware agents that read your ERP, draft a sales order from a PDF or an email, answer finance questions in plain language, and with a human approving write back to the ERP. Every action runs behind a fail-closed permission boundary, with human-in-the-loop approvals and a full audit trail.
Finance copilot
Plain-language Q&A over live ERP data, cited to source.
PO → Sales-order agent
Reads a customer PO, matches items and contracted pricing, flags exceptions, drafts the order for approval.
Project forecaster
Variance and what-if over live project budgets and actuals.
Email intake
Turns an emailed document into a structured, review-ready draft.
MCP in Teams / Copilot
The same agents, reached from where your team works.
Full audit trail
Every read and write, logged and exportable.
Questions we get asked about AI Agents & Automation.
What is an AI agent?
An agent does more than answer questions. It takes a goal, works out the steps, gathers what it needs across your systems, does the work, and hands you the result for approval. A real example: draft the sales order from this purchase order, match the customer’s contracted pricing, flag anything that doesn’t reconcile, and queue it for approval.
What is the difference between AI agents and RPA?
RPA follows fixed scripts, so it breaks when a form or format changes. Agent-based automation pairs those deterministic steps with a model that can read intent, handle exceptions and explain its reasoning. When a document doesn’t match the template, the agent flags it and keeps the queue moving. One governed platform then handles both the routine work and the judgment calls.
What is the Model Context Protocol (MCP)?
MCP is an open standard for connecting business systems to AI assistants such as Claude and Microsoft Copilot. Set up properly, the user’s identity and permissions travel with every request, so answers stay within what that person is allowed to see. Sage Intacct now has a native MCP server, and SAP is exposing agents over MCP and A2A.
Can AI agents run inside Microsoft Teams and Copilot?
Yes. We build an agent once on a governed platform, then deliver it where your team already works: Microsoft Teams, Microsoft 365 Copilot, a web app, or Claude via MCP. On every surface the agent acts as the person who invoked it, with that person’s access. There is no shared AI account with access to everything.
Can an AI agent write data back to our ERP?
Yes, within guardrails. The agent drafts the write, a person reviews and approves it, and only then does anything post. Nothing posts automatically. A fail-closed permission boundary sits behind every action, and an audit trail records who asked, what was read and what was posted. This is the pattern we run in beta on our own platform today.
How long does it take to build a custom AI agent?
It usually starts with the two-week AI Value Workshop, which finds and ranks the highest-value candidates. A first, tightly scoped agent is then typically a matter of weeks. Every build is scoped and quoted before it starts, and it ships with permissions, approvals and audit in place from day one.
Get in Touch
Want to know more about SAP Cloud ERP? Contact the SAP Cloud ERP team at Leverage Technologies on