Drona is a production-intelligence system for manufacturers with order-driven supply chains.

It helps teams determine whether a specific order can be produced and delivered on time, which dependencies require attention, and what action remains available when conditions change. The assessment is built around the actual commitment—not a permanent or generic supplier score.

Drona begins with the order and works through the components, suppliers, production stages, materials and external dependencies required to fulfil it.

It establishes what must remain true for the order to succeed, what could break those conditions, and what evidence would change the assessment. This creates an order-specific view of production reliability and helps teams concentrate attention where it can still affect the outcome.

Drona does not begin by trying to map everything. It works with the manufacturer to identify the components and commitments whose failure would materially affect production or delivery.

It then traces the suppliers, facilities, materials, processes and sub-tier relationships behind them. Factors such as consequence, substitutability, lead time, concentration and the time remaining to respond help determine what is critical.

As far as the decision requires.

Drona looks beyond Tier 1 when a lower-tier material, processor, facility, route or single-source dependency can control the outcome of an order. Broader network mapping can deepen over time, but critical dependencies come first. The objective is decision-useful visibility—not completeness for its own sake.

Drona can monitor financial, commodity, geopolitical, regulatory, logistics, climate and location-specific risks.

It does not treat every external event as an alert. A warning becomes relevant when it connects to a real dependency, could materially affect production or delivery, can be tested against available evidence, and reaches the team while a useful response is still possible.

Yes—with the manufacturer’s approval.

Drona can recommend a proportionate response, such as requesting additional evidence, securing an input earlier, escalating a production milestone or opening a working-capital pathway. It can then contact the relevant supplier through email, messaging or voice to explain the concern and coordinate the next step.

The manufacturer retains control over external communication and final action. The supplier retains responsibility for its operational decisions.

A viable order can still fail when a supplier cannot fund the materials or production activity required to complete it.

Drona connects a finance request to the underlying order, production requirements, milestones and relevant risks. This gives the financier a clearer evidence package and gives the manufacturer an earlier opportunity to address a cash constraint before it becomes a production delay.

Kanan does not lend, guarantee approval or make the credit decision. The regulated financier does.

That is a core design requirement.

Every material assessment is intended to remain connected to its supporting evidence, the dependency being evaluated, the reasoning applied and the uncertainty that remains. Where the evidence is insufficient, Drona should surface the gap or request review—not manufacture certainty.

AI can assist with analysis and coordination. It does not replace evidence, accountability or human authority.

Drona is designed to work alongside existing procurement, ERP, supplier, quality and finance workflows—not replace them.

A deployment can begin with one bounded order and an agreed set of documents, supplier records and production evidence. Suppliers can be engaged through familiar channels, while internal teams retain their existing responsibilities and approval rights. Integration can deepen where it reduces work and improves the quality of the decision.

Drona is currently in the design-partner phase.

Kanan has a defined product thesis and operating model. Its performance, integrations and production-stage logic must now be tested against real manufacturing conditions.

A design partnership typically begins with a bounded live or shadow-live order, agreed data boundaries and clear success measures. Kanan and the manufacturer then review what became knowable, when it became actionable and whether the assessment improved the response. It is a structured product-validation engagement—not an open-ended consulting exercise.