Causal AI for Chemical & Pharmaceuticals
Building a sustainable future
The chemical and pharmaceutical industry stand to gain significant advantages by leveraging Causal AI. This novel approach enables businesses in these sectors to make more accurate predictions, optimize processes, and accelerate innovation.
In drug discovery, causal AI can identify causal factors driving complex biological processes, enabling faster identification of potential treatments. In chemical manufacturing, it can optimize production processes by uncovering the root causes of inefficiencies or defects, reducing waste, and improving yield.
By harnessing causal AI, these industries can gain a competitive edge, drive innovation, and achieve more efficient and cost-effective operations.
Total economic benefit
Golden Batch
Quality Optimization
Data Governance
Mapping & Data Quality
Golden batch quality optimization
A Fortune 500 Biologics major implemented a Causal AI based root cause analysis system to optimize batch variations in bio-reactor’s yield, quality, and to minimize batch rejections using TRAIN.
The AI agent utilizes causal knowledge to continuously monitor batches against the “golden batch” profile. It provides guidance on input feed rate and specific process adjustments referencing the “Golden Batch”.
This implementation resulted in minimizing variations in batch cycle time and replicating the golden batch to enhance product quality. The easy to simulate process twin helps in understanding the complex interactions within production processes allowing for real-time simulation and analysis.
Total economic benefit
15 Seconds
Root cause analysis
16%
Reduction in batch quality variations
15 Seconds
Scenario simulations
Enterprise Data Governance
A Fortune 500 chemical major implemented a Causal AI based metadata discovery, mapping, classification and grouping solution to expand the coverage of enterprise data governance.
The traditional manual approach required data stewards spending 1000’s of hours interviewing the data users to understand the context and usage of the data. This process is extremely time confusing and requires intricate knowledge of the business.
The AI agent enables data stewards to automatically discover business concepts, contextually map with physical data and curate definitions for expanding the coverage of Enterprise Data Governance(EDG).
Total economic benefit
Data Quality
Mapping+Definitions
Mapping
Technical-to-Business Metadata
Contextual
Grouping
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Learn more about how Causal AI can empower your teams to
- Maximize touchless order processing and reduce OTIF penalties.
- Optimize Procurement planning and maximizing mill throughput.
- Minimize shop floor incidents to ensure workers safety.
- Minimize energy consumption and achieve de-carbonization goals.
- Harmonize technical and customer facing information for product/system design optimization.