The EU carbon border mechanism is in force, so your customers now have to declare the emissions embedded in what they buy from you, and those figures can only come from your plant. We deploy AI agents that assemble them from your production, quality and energy systems, with an audit trail on every number. Deployed in your infrastructure.
The plant that wins the order is not always the one with the lowest cost. Increasingly it is the one that can prove things: carbon per product, batch traceability, quality records, delivered in the format the customer's auditor expects. None of that sits in one system today. We build the layer that turns what your machines, your MES and your ERP already produce into evidence your customers accept.
The problems we solve every day for organizations like yours.
The EU carbon border mechanism now applies to iron and steel, aluminium, cement, fertilisers, electricity and hydrogen, and your European customer has to declare and offset the emissions embedded in what they import from you. For the rest of industry the buyer is asking anyway. The figures per product can only come from your plant, and nobody there has time to assemble them.
Quality records, batch traceability, PPAP and 8D files, maintenance histories, certificates. When a customer's auditor picks one batch and follows it end to end, the answer is assembled by hand from the MES, the ERP, paper travellers and email. The larger the customer, the more often they ask, and the shorter the notice.
A single equipment failure stops a line and cascades through the schedule. Maintenance is either too early, wasting parts, or too late, costing production. The signals that would have predicted it are already in your machine data, and nobody has time to watch them.
Machines, MES, ERP and spreadsheets each hold a piece of the picture. Reporting becomes a manual reconciliation, and by the time it reaches a decision it is already out of date. Integration is the precondition for everything above, and it is the part generic AI tools skip.
The requirements arriving at Tunisian plants are specific, dated and written down. These are the ones we design against.
The EU carbon border mechanism applies to iron and steel, aluminium, cement, fertilisers, electricity and hydrogen. Your European customer must declare and offset the embedded emissions of what they import from you, so your product-level carbon figures have become part of the commercial relationship, not a voluntary report.
Textile and automotive suppliers meet the same direction of travel through different instruments: buyers' sustainability and traceability clauses, and product-level data increasingly requested in tenders. The direction is one way, and the format is set by your customer's own reporting.
For automotive suppliers, IATF 16949 and customer-specific requirements drive audits, PPAP and 8D. Our systems keep that evidence in one traceable place instead of reconstructing it for every audit.
Tunisia committed to a 41% cut in emissions by 2030, with green financing from the GCF, EIB, AFD and EBRD tied to measurable data. Automotive components alone account for 300 companies, 120,000 jobs and 3.5 billion dollars in exports, so the data question reaches a large part of Tunisian industry.
Concrete applications that deliver measurable outcomes.
Assemble per-product carbon and energy figures from production, energy and purchasing data, in the format your customers and their auditors accept.
Build batch records, PPAP and 8D evidence from the MES, the ERP and manual records into one file you can hand to an auditor.
Detect degradation patterns from machine and sensor data so interventions happen before failure, not after.
Inspect parts consistently at line speed, catching defects earlier and reducing scrap and rework.
Our core solutions tailored to the requirements of your sector.
Assistants that put technical knowledge, procedures and maintenance history at the fingertips of operators and maintenance teams.
Automate the data flows between the shop floor and your business systems, so reporting and evidence assemble themselves.
Predictive and inspection systems engineered for your lines, your constraints and your uptime targets.
No. We read from your machines and systems, we do not write to them. Deployment is one-directional and segmented from your OT network, on your own infrastructure, so nothing we run can move a line.
That is the normal starting point. We begin with what exists, machine signals, MES exports, spreadsheets and paper, and the first deliverable is a pipeline that produces one trustworthy figure rather than a dashboard over unreliable ones.
No. We connect through documented interfaces to what you already run. No migration, no replacement, and no retraining for your planners.
In your infrastructure, under your control. We do not train models on your process data, and your customer's figures are produced from your data, not from an industry average.
Predictions and flags are advisory. A human decides, thresholds are set with your maintenance and quality leads, and a model can be pulled from the flow without stopping the line.