Operationalizing AI for life sciences-beyond pilots
AI solutions and fluency framework

Operationalizing AI for life sciences-beyond pilots

AI isn’t failing due to lack of ambition. 
It’s failing due to lack of operationalization. 
Operationalizing AI for life sciences-beyond pilots
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AI solutions and fluency framework

Operationalizing AI for life sciences-beyond pilots

AI isn’t failing due to lack of ambition. 
It’s failing due to lack of operationalization. 

Move from fragmented pilots to enterprise AI solutions through consulting, implementation, and support and training with AI labs- An AI R&D wing built for life sciences. 

Looking to increase your organization’s AI fluency?

But stuck with

The i2e approach

From planning to scaling - end-to-end 

Consulting: Define the AI operating model

Align AI with business priorities, design governance for AI-ready data, and identify high-value use cases

Implementation: Build and integrate

Develop AI solutions and embed them into your existing systems and workflows, start with one department and scale.

AI Labs: Accelerate and industrialize 

Rapidly prototype, validate, and scale use cases, while building internal AI fluency

Continuous Support: Sustain and evolve

Govern, optimize, and expand AI adoption across the enterprise

Business Impact 

Future-ready AI operating model 

Connected and AI-ready data

AI agents enabling cross-functional visibility

Uniform AI fluency across all departments

Success stories

A global pharma company saves time and improves the success of clinical trial protocols using AI and ML

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Transforming PMO daily standups with an Agentic AI project manager

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A Generative AI Chatbot Streamlines Clinical Trial Operations for a Pharma Organization

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Our services

Strategy & AI operating model 

  • AI maturity assessment 
  • AI use case discovery  
  • AI operating model design 
  • Build vs buy vs partner strategy  
  • AI roadmap with value prioritization 

Data foundation for AI (AI Readiness)

  • Data discovery, integration, and harmonization  
  • Structuring unstructured content  
  • Metadata, ontology, and knowledge graph design  
  • Data governance and lineage frameworks  
  • AI-ready data platforms (often on SharePoint, cloud, etc.) 

AI solution development

  • AI/ML models and GenAI solutions 
  • Model development, training, and validation
  • Automation of insights, decisioning, and processes
  • Cognitive dashboards for faster decision making 
  • Reusable components for rapid deployment

AI Integration & Engineering

  • Integration with existing systems
  • API orchestration and workflow automation
  • MLOps / LLMOps setup (deployment, monitoring, retraining)  
  • Scalable architecture design 

Responsible AI & Compliance

  • GxP-aligned AI validation frameworks  
  • Model explainability and audit trails  
  • Data privacy (HIPAA/GDPR) compliance  
  • Risk management and governance policies

AI fluency & Change management

  • Role-based AI training (scientists, PMs, leadership)
  • AI playbooks and workflow redesign
  • Co-pilot adoption strategies
  • Change management and communication

Managed AI services (Run & Scale)

  • Ongoing model monitoring and optimization  
  • Use case expansion roadmap  
  • Performance tracking and ROI measurement  
  • Support and enhancements 

Ready to move beyond AI pilots?  See how i2e can help you operationalize AI across your organization. 

Contact us

FAQs

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