What we build: five AI capabilities for your operations.
Each one comes with a complete example, a preview of what it produces and the systems it connects to. They combine to fit your process.
Five capabilities, one way of working.
Open each one for a complete example, what it produces, what it connects to and its safeguards.
Intelligent Agents
Which tasks take hours of looking things up across several systems?
Support a task end to end, connected to your business applications.
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A complete example
A buyer asks where an order stands. The agent checks the order in the ERP, the supplier's last email and the delivery note, then drafts the reply with its sources. The buyer reads it and sends it.
Where do simple cases wait in a queue behind complex ones?
Business workflows that combine rules and AI.
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A complete example
Customer claims arrive by email. Rules settle the standard ones, such as a missing item under the approved threshold; a model classifies the others and sends each to the right team with a summary.
Illustrative preview
Incoming claim · routing
TypeMissing item, standard case
Rule appliedReplacement under the approved threshold
Which business questions still take a spreadsheet and two days?
Make sense of the data you already hold, to decide.
More detailsFewer details
A complete example
The sales director asks which customers lost margin this quarter, and why. The answer lists them with their figures, the definition of margin used and the source of each line, so finance can check it.
Illustrative preview
Question · margin by customer this quarter
AnswerCustomers below target margin, listed with their figures
DefinitionMargin after rebates, as agreed with finance
How many documents are still read, sorted and keyed by hand?
OCR, classification and extraction for your document flows.
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A complete example
A supplier invoice arrives as a PDF. It is read, classified as an invoice, its fields are extracted and matched with the purchase order. If a field is unclear, the invoice goes to review instead of being keyed by hand.
Illustrative preview
Supplier invoice · extracted fields
SupplierRead and matched with the supplier record
Amounts and VATRead, totals consistent
Order referenceUnclear on the scan: sent to review
Classified as an invoice · sent to accounts payable
Where does planning still depend on one person's experience?
Rule engines for allocation and scheduling.
More detailsFewer details
A complete example
For next week's production, the engine proposes a sequence that groups similar products on each line, shows what it gains in changeovers against what it costs in delivery dates, and the planner adjusts it.
Illustrative preview
Proposed plan · next week
SequenceSimilar products grouped on each line
Trade-offFewer changeovers; two orders ship a day later
Margin anomaly detection, read in five stages: what the system reads, what it infers, what it recommends, who approves it and what is measured afterwards.
Illustrative scenario
01
Signal
Invoice lines, price-list versions, discount grids and freight costs, read from the systems you already run.
02
Understand
A group of lines priced outside the approved grid, sharing one customer group and region. Below the confidence threshold, it goes to review, not to action.
03
Decide
Hold the lines before credit notes are issued and correct the price-list fault upstream, with the reason stated.
04
Act
Flag the lines in the ERPAutomated
Open a controlling taskAutomated
Release the credit notesApproval
Renegotiate the contractEscalated
Nothing financially irreversible runs without a named approver.
05
Measure
Margin leakage and detection lead time, compared with the starting point agreed at the outset.
The whole use case
Margin anomaly detection: the problem, who decides and the result to expect.
Governance is not a sixth capability: it applies to all five. For every use case, each action sits at one of these levels.
For each use case we also set the data it may access and the record it leaves behind. We describe our own practice; we claim no certification that has not been issued.
Automated
The system acts alone, within limits written in advance, and records what it did.
Recommended
The system proposes, with its reason. A person decides.
Approved
Nothing happens until a named person approves it.
Escalated
Outside the limits, the case goes to the person who owns the decision.
AI doesn't replace your environment. It works inside it.
Your ERP stays your system of record. The intelligence layer reads from it, reasons over it and writes back into the workflows your teams already use, under the same permissions.
The value isn't the model. It's knowing what should stay standard, what must be integrated, what needs engineering and what can reasonably be automated, and being able to run the result afterwards.
Your environment
ERP (Dynamics 365 / Business Central) and other systems of record
CRM and operational applications
Documents and procedures
Data platform and APIs
Business rules
Intelligence layer · inovasys.ai
Models and retrieval
Agents and tool access
Automation
Decision logic and thresholds
Evaluation and monitoring
Governance and audit trail
Back into operations
Users, in their own tools
Approval and escalation steps
Applications and workflows
Field and operations teams
Measurement against the starting point
Built and run with the other two universes
Bespoke engineering comes from inovasys.io; deployment and long-term operation from inovasys.ma.
