Kovant provides an agentic platform that deploys autonomous AI digital workers to run enterprise supply-chain operations, from procurement to inventory and production planning. The platform replaces brittle workflow automation with role-based execution, where agents handle exceptions, communicate through existing tools like Microsoft Teams and Slack, and escalate only true exceptions to humans. Kovant integrates with existing infrastructure without rip-and-replace, delivering operational capacity in weeks, not months.
Funding
€1.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AEMGVSHFounders
Product
Problem
Enterprise supply-chain operations remain heavily dependent on manual processes and brittle, scripted workflow automation that breaks when exceptions occur. Unstructured inputs like emails and documents, combined with siloed systems, make it difficult for organizations to scale operations efficiently and respond dynamically to change.
Solution
Kovant provides an agentic platform that deploys teams of autonomous AI agents as digital workers to run enterprise supply-chain operations end-to-end. The platform uses role-based execution, where agents are defined by job descriptions, policies, and escalation rules, rather than rigid workflows. Kovant agents handle variation, communicate through familiar channels like Microsoft Teams, Slack, and email, and escalate only true exceptions to humans. The platform includes built-in governance, audit trails, and human oversight, and can be deployed in weeks without development or rip-and-replace, enabling immediate operational capacity.
Target Audience
Primary customers are enterprise organizations in industrial, manufacturing, and supply-chain-intensive sectors, including procurement, inventory, production, and aftermarket service operations, seeking to modernize their operational core with autonomous AI execution.
Features
- Twelve foundation agents combine into cross-functional teams that plan, communicate, and execute under human oversight, scaling across operations and adapting to exceptions.
- Constraint-aware capacity modeling evaluates machine capabilities, labor availability, shift schedules, and material supply simultaneously to generate realistic capacity plans.
- Demand-driven scenario planning analyzes historical production data, forward order books, and market signals to simulate capacity scenarios and identify emerging constraints.
- Condition-based maintenance scheduling generates rolling maintenance plans from asset health signals, OEM intervals, and production commitments, automatically creating work orders.
- Spare parts planning projects requirements from maintenance schedules and supplier lead times, triggering procurement before stock-outs occur.
- Agents track utilization rates, work-in-progress levels, and lead times across lines and workcenters, flagging queue imbalances and capacity variances proactively.
- Model-agnostic architecture supports Small Language Models (SLMs) to reduce hallucination risk, with ISO-certified security and optional deployment in the customer's own cloud tenant.
- Accessible through Microsoft Teams, Slack, and email, with a central Agent Hub for interaction and management.