AI Solutions

From zero to AI-ready. On data you control.

Buying Claude, ChatGPT, or Copilot is not an AI strategy. Marquis IQ AI Solutions give manufacturers a governed path to enterprise data analysis: trusted ERP numbers, a semantic layer that controls inferences, MCP into the tools your team already uses, and security and audit from day one.

Stay in control
Your modelsClaude, ChatGPT, Cursor, Copilot, Excel AI
Marquis IQ MCPGoverned questions, not raw ERP dumps
Semantic layerYour definitions of margin, backlog, inventory
Security & auditDataset, row, column. Who asked what.
The wrong answer

A chatbot subscription is not an AI strategy for enterprise analysis.

Teams are being told to “just get Claude.” That gets you a model. It does not get you trusted ERP context, controlled definitions, or a way to stay in control of what AI is allowed to see and infer.

What buying a model gets you

A capable assistant. Spreadsheet uploads. Guesswork on customer names, item numbers, and which plant’s inventory is real. No agreement on what “margin” means. No record of who asked what. No row or column controls.

What an AI strategy requires

Clean multi-ERP data. A semantic layer so inferences use your definitions. Dataset, row, and column security. Audit. Tool choice that can change next year. Marquis IQ is that layer. The model is a client.

AI Solutions

Use AI for analysis and strategy. Not just email and marketing copy.

Ask the questions your board already asks, in the tools people already open, against one governed model of the business.

Finance and cash

Aging, collections risk, working capital tied up in inventory and AR. Same numbers Finance IQ already uses.

Margin and pricing

Price, volume, and mix on trusted transactions. Why gross margin moved, by customer, item, and plant.

Inventory and operations

Days on hand, slow movers, open orders at risk. Daily questions without a new dashboard project.

Sales and procurement

Customer and supplier families that actually match across ERPs. Spend, price variance, at-risk accounts.

Complex, follow-up analysis

Start in Claude or ChatGPT, continue in Excel AI, or work in Cursor. Same semantic layer. Same security.

Strategy, not slides

Scenario questions on governed history: where mix is diluting margin, which sites are absorbing the cash.

Questions you can ask

Because the model is governed, the answers can be trusted.

Examples tied to IQ Modules. AI does not invent a second set of books. It uses Marquis IQ.

Which customers are past due over 60 days after we roll them up to the mastered parent?
Where did margin move last quarter, and was it price, volume, or mix?
Which items are over 180 days on hand by plant, and what working capital is tied up?
Which open orders are at risk this week, and what is the dollar exposure?
Which suppliers overlap across ERPs, and where can we consolidate spend?
Which customer families declined more than 10% versus prior year, after de-duplication?
Implementation

A rapid path from zero to AI-ready. Security on from day one.

Marquis enables adoption. We are not a generic systems integrator. Connect ERPs, master and enrich, publish a semantic layer, then open MCP into the AI tools you choose. Weeks to first governed questions, consistent with how Marquis IQ already goes live, not a new invented timeline.

1

Connect

Certified connectors to the ERPs you already run. Current data, not a one-off extract.

2

Master and enrich

One customer, supplier, and item across entities. This is why AI answers do not split the same account three ways.

3

Semantic layer

Your definitions of revenue, margin, backlog, and inventory. Inferences you control, not the model’s guess.

4

MCP into AI tools

Claude, ChatGPT, Cursor, Copilot, Excel AI. Dataset, row, and column security plus interaction audit, on from the first question.

In control

Tool-agnostic. Semantics you own. Security you can explain.

Stay in control of enterprise AI analysis. Spend visibility is one proof, not the reason to buy.

Tool-agnostic

The model is a choice. MCP is the interface. Switch clients without rebuilding a data strategy.

Semantic / AI metadata

Margin means what your finance team means. AI uses those definitions instead of improvising them.

Dataset, row, and column

Administrators decide which datasets, attributes, and rows each user can reach through MCP.

Audit

Who asked what, on which data. MCP interactions are stored for transparency and compliance.

Spend visibility

Know what AI usage is costing. One of several ways you remain in control, not the headline.

Trusted numbers

Trusted means governed data, plus semantics, plus security. Not a slogan without those three.

Get from zero to AI-ready. Securely.

We will show how Marquis IQ AI Solutions put analysis in Claude, ChatGPT, Cursor, Copilot, and Excel on the same governed ERP foundation your team already needs, with MCP as the implementation interface.