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Accelerating Clinical Collaboration with Contextual Conversational AI

Impact Delivered

  • 40% Faster issue resolution
  • 35% Fewer repeat explanations
  • 30% Productivity improvement
  • 25% Better decision quality
  • The Customer

    The Customer

    Clinical Trials teams at a large pharma organization collaborating across documents, emails, and chats who need conversations to retain prior findings, decisions, and references—so multiple stakeholders (medical writers, safety, regulatory) can align quickly without re-explaining context.

  • The Challenge

    The Challenge

    3D-Priniting-Challenges-Img.jpg

    Maintain end-to-end conversational context and traceability so teams can:

    • Avoid context loss when switching among documents, email threads, and chat tools.
    • Reuse prior discussions and decisions without duplication.
    • Locate original source passages and citations quickly for audit and review.
  • The Solution

    The Solution

    the-solution-img_nextiva.jpg

    Enable a contextual chatbot workspace (deployed on the platform) that preserves and surfaces prior knowledge:

    • Upload and embed medical documents for in-chat reference and grounding.
    • Apply context filters, generate prompts, and surface FAQs on demand.
    • Persist session history so users can resume threads with full context.
  • Solution Components

    Solution Components

    LLMs; Document embedding; Contextual filtering; Session persistence

  • The Results

    The Results

    • Continuous context across documents and sessions
    • Reduced rework and miscommunication
    • Faster, more consistent clinical analysis

Impact Delivered

  • 40% Faster issue resolution
  • 35% Fewer repeat explanations
  • 30% Productivity improvement
  • 25% Better decision quality

The Customer

Clinical Trials teams at a large pharma organization collaborating across documents, emails, and chats who need conversations to retain prior findings, decisions, and references—so multiple stakeholders (medical writers, safety, regulatory) can align quickly without re-explaining context.

The Challenge

3D-Priniting-Challenges-Img.jpg

Maintain end-to-end conversational context and traceability so teams can:

  • Avoid context loss when switching among documents, email threads, and chat tools.
  • Reuse prior discussions and decisions without duplication.
  • Locate original source passages and citations quickly for audit and review.

The Solution

the-solution-img_nextiva.jpg

Enable a contextual chatbot workspace (deployed on the platform) that preserves and surfaces prior knowledge:

  • Upload and embed medical documents for in-chat reference and grounding.
  • Apply context filters, generate prompts, and surface FAQs on demand.
  • Persist session history so users can resume threads with full context.

Solution Components

LLMs; Document embedding; Contextual filtering; Session persistence

The Results

  • Continuous context across documents and sessions
  • Reduced rework and miscommunication
  • Faster, more consistent clinical analysis
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