ERP provider inecta announced on June 3 the launch of inecta AI Agents, a configurable AI automation platform for food and beverage companies running inecta Food ERP. inecta said most existing inecta Food ERP customers can deploy their first production-ready agent within a week, without custom development or coding.
The platform is designed for food manufacturers, processors, distributors, and seafood operators. It automates operational workflows including AP invoice intake, sales order entry, document processing, quote generation, internal lookups, and exception routing.
“Food businesses don’t need another disconnected AI assistant, they need automation that actually works inside their operations,” said Ruth Lestina, COO of inecta. “inecta AI Agents gives operators a practical way to automate repetitive ERP workflows without the cost and complexity of custom AI projects.”
Agents Work Inside the ERP Data Model
The key distinction is where the agents operate.
inecta said the agents run natively inside the inecta Food ERP data model, rather than acting as a disconnected AI assistant or external robotic process automation layer. Agents can read and write ERP records, process inbound emails and documents, draft responses, and execute scheduled workflows while following existing posting rules, approval chains, audit requirements, and entity-level permissions.
On its product page, inecta describes the platform as built for Microsoft Dynamics 365 Business Central. The company said inecta AI Agents are available for any Business Central environment, with deeper out-of-the-box knowledge of inecta Food ERP workflows for food and beverage customers.
The platform supports manual, chat, email, and scheduled triggers. Agents can run on demand, respond through chat, monitor an inbox, or execute recurring workflows based on a schedule.
Food Workflows Define the Agent Scope
inecta is positioning the product around food-industry operating requirements, not horizontal back-office automation alone.
The platform includes native support for lot traceability, catch weight processing, vessel and quota management, recipe and production workflows, and quality control operations. inecta’s product documentation also lists food ERP agents for QC, lot traceability, catch weight, EDI, production, customer service, inventory, purchasing, and related workflows.
Food and beverage ERP environments often involve operational constraints that generic automation tools may not understand. Lot investigations, quality holds, catch-weight variance, supplier quality trends, failed EDI documents, production shortages, and open corrective actions all require process context from the ERP system.
For example, a lot traceability agent can summarize related receipts, production, shipments, and affected customers during an investigation. A catch weight agent can flag unusual yield, weight variance, or margin impact. A QC agent can monitor failed quality tests, open holds, supplier quality trends, and unresolved corrective actions.
Governance Controls Sit Around Writeback
inecta is also emphasizing control over what agents can access and do.
Each agent reportedly can be configured with scoped permissions across Business Central or inecta Food ERP entities. Agents can be read-only or action-enabled, with write access granted only where explicitly allowed. Every run is logged with inputs, actions, and outcomes for review and accountability.
The company also says approval-required gating for high-impact actions is on the roadmap. That point is important because ERP agents that write into systems of record create a different risk profile than chatbots that only summarize information.
What This Means for ERP Insiders
Industry ERP is an agent deployment layer. inecta is not presenting AI agents as a separate productivity tool; it is embedding them into food ERP workflows where invoices, orders, quality checks, lot records, and production data already live. Vertical process context will become a key differentiator in agentic AI.
Permission design will determine automation trust. inecta’s model gives agents scoped access to ERP entities, read/write controls, audit history, and trigger settings, which are the controls needed before AI can act inside systems of record. Agent governance needs to be designed at the data model, workflow, and approval-chain level.
Food ERP gives agentic AI a practical proving ground. Food manufacturers and distributors deal with traceability, catch weight, quality control, EDI exceptions, and production variability that create repetitive but high-consequence workflows. Agentic AI will gain traction fastest where automation can reduce manual effort while preserving compliance, auditability, and operational control.
