API stockouts and batch failures
caught 30 days earlier.
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<24 hrs
Batch Rejection Detection
Pattern detected by AI
+30 dayswarning
Supply Risk Lead Time
Before disruption hits
0–100
API Supplier Risk Score
Per supplier, per API
12 daysearly
Inventory Imbalance Alert
Before stockout
Real Pain → AI Solves It
Your team faces these every week.
OpsOracle names them and fixes them.
Actual AI output from real pharmaceutical supply chain data. Upload your report and get this analysis in under 30 seconds.
The Pain
One of our critical API suppliers is sole-source. Any disruption stops 3 formulations. Procurement has no visibility into their risk.
Raw data signal
Supplier: ChemIndia Ltd | API: Paracetamol API | Lead time: 45 days | Last delivery: On time | Dependency: 100% | Inventory: 22 days stock | MOQ: 2000 kg
OpsOracle AI Output
ChemIndia Ltd is sole-source for Paracetamol API with only 22 days of buffer stock — below the 30-day minimum for uninterrupted production. 45-day lead time + 22-day inventory = 0-day safety window if any disruption occurs. 3 formulations stop simultaneously. This is a regulatory and revenue risk: stockout = batch failure + potential recall.
[THIS WEEK] Action
Emergency: qualify alternate API supplier this quarter. Increase safety stock to 60 days (4000 kg immediate purchase). Negotiate vendor-managed inventory agreement with ChemIndia to gain 14-day early warning on supply delays. File alternate source with CDSCO within 90 days.
Expected impact: Prevent 3-formulation production halt worth ₹1.2–2.4Cr/month in lost output. Eliminate CDSCO non-compliance risk from supply disruption.
The Pain
Batch rejection rate jumped from 1.2% to 4.8% this month. QA is investigating but no patterns found yet.
Raw data signal
Batch #1–20: Rejection rate 1.2% | Batch #21–40: Rejection rate 3.1% | Batch #41–55: Rejection rate 4.8% | Rejected: Dissolution failure 7 batches | API lot changed: Batch #22 | Temperature excursion: Cold room C batch 38–40
OpsOracle AI Output
Rejection rate is escalating in 3 discrete steps — not random. Two correlated events: (1) API lot change at Batch #22 coincides with first rejection spike; (2) Temperature excursion in Cold Room C covers Batches 38–40, the highest rejection cluster. Dissolution failures are consistent with either API potency variation or stability compromise from temperature breach.
[THIS WEEK] Action
QA to compare API CoA across lot pre/post Batch #22 — focus on particle size distribution and dissolution profile. Cold Room C: audit temperature logger for Batches 38–40, quarantine if excursion confirmed, test retained samples. Report to QP before next batch release.
Expected impact: Prevent further ₹48L in rejected batch losses this month. Avoid regulatory trigger if pattern continues — 5% batch rejection typically triggers CDSCO audit.
The Pain
We have 6 months of finished goods inventory for Product X but stockout risk on Product Y which shares the same packing line.
Raw data signal
Product X: 180 days inventory | Monthly demand: 8000 units | Packing line utilisation: 62% for X. Product Y: 12 days inventory | Monthly demand: 22,000 units | Packing line: shared with X | Lead time: 35 days
OpsOracle AI Output
Product X holding 180 days stock (6× optimal 30-day buffer) while Product Y has only 12 days — below critical threshold given 35-day replenishment lead time. With shared packing line at 62% utilisation on X, Product Y is being crowded out. At current schedule, Product Y stockout in 12 days before any new production run completes.
[THIS WEEK] Action
Immediate: reduce Product X packing schedule to 20% of line capacity. Dedicate 80% to Product Y for next 21 days to build buffer to 45 days. Commercial team to review Product X sales velocity — 180-day stock at 8K units/month suggests demand forecast error.
Expected impact: Prevent Product Y stockout (₹44L/month revenue at risk). Free ₹28L in Product X working capital by correcting over-production.
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