Planning without material truth
Schedules move faster than reservations, shelf life, alternates, and incoming inspection.
AI-native manufacturing ERPTrace control / 01
One operating system for traceability-heavy electronics and pharma—from the first demand signal to the final shipment record.
Component lot L-782 has 9 hours of approved floor life remaining.
Evidence chain14 linked recordsLast event 10:42:18
Orders, material, execution, quality, and release live in different rhythms. Every handoff asks someone to reconstruct what happened.
Schedules move faster than reservations, shelf life, alternates, and incoming inspection.
Operators receive a job, but not the approved revision, deviation, or upstream risk.
Quality assembles evidence after the work instead of inheriting it from the process.
Prakriya carries identity, status, exceptions, approvals, and provenance forward—so the next team starts with context, not a search.
Orders, forecasts, revisions, priorities
MRP, capacity, pegging, commitments
Lots, shelf life, inspection, reservation
Work orders, routing, consumption, output
Tests, nonconformance, disposition, release
Serialization, documents, customer trace
The agent reads permitted operational context, explains the evidence, prepares a bounded action, and waits for the right person to approve it.
Read live operational signals and linked records.
Show why the signal matters and cite its source.
Draft a reversible action within defined scope.
Route consequential changes to an accountable human.
MCP integration plane
Model Context Protocol servers expose approved tools and resources through a controlled gateway. Identity, scope, and audit remain attached to every request.
The core trace stays continuous. The operating details adapt to what electronics and pharma teams must control.
Typical evidence: component lot → placement → test result → assembly serial.
Typical evidence: material batch → dispense → process check → finished batch.
Prakriya is designed around explicit roles, bounded actions, approval gates, and durable audit trails. AI participates in the same operating discipline as every person and process.
Book a factory walkthroughThe next shift can start with context.