SCIMAX ARIN

Response Recommender

Recommends the most relevant FAQs and response documents to use for fulfilment (based on the question and historical data).

Provide Rapid, Accurate Medical Responses Powered by AI

The deluge of varied questions day in and day out that your Medical Information team receive from HCPs, patients and stakeholders can be overwhelming. Reacting fast and accurately is crucial, but when you have to spend hours searching through thousands of documents and FAQs, your team is slowed down, errors are introduced, and compliance is at risk. The ARIN’s Response Recommender agent transforms this by automatically suggesting the most applicable FAQs and response material based on context of inquiry and past case data.

Key Benefits

Features

Contextual Inquiry Analysis

Leverages powerful language models to understand full context and purpose of all questions via email, webform, phone call or CRM. This level of insight goes beyond keywords to guarantee that recommendations are genuinely relevant to what your audience requires.

Intelligent Document Recommendation

Automatically brings up the most relevant FAQs and response files from your growing knowledge base on-the-fly. Recommendations are ranked through machine learning models considering inquiry similarity, previous case outcomes and user feedback to ensure best-fit options are always presented to your team.

Performance Tracking and Learning Engine

Integrated analytics dashboards show most common responses, where escalation to medical professionals happens, and how satisfied users are with AI-provided solutions. The agent continuously learns from your feedback so that it can improve its recommendations over time, and help your medical information team to continue achieving industry-leading quality and efficiency.

Explore other ARIN Agents

Email Triage Engine

The agent automates the triaging of unstructured emails into cases arriving in MedInfo mailboxes for MedInfo teams.

Response Recommender

Recommends the most relevant FAQs and response documents to use for fulfilment (based on the question and historical data).

Response Package Composer

Assembles a complete response package with the appropriate documents, templates, and formats for MedInfo teams to review.

Response Fulfilment Engine

Creates and sends a response package to the HCP, including relevant response documents, enclosures, and covering letters.

AE and PC Dispatcher

Automatically creates AE and PC reports and forwards them to the appropriate end systems or departments for next steps.

Predictive QA Engine

Utilizes predictive analytics using case data to reveal unidentified Adverse Events or Product Complaints.

Retrospective QA Engine

Archived cases are re-reviewed to identify any such Adverse Events and Product Complaints that may have been overlooked during review of the original cases.

Medical Information Smart Chatbots

Medical Information Smart Chatbot agent acts as a digital front line, instantly addressing frequently asked medical queries, ensuring regulatory-compliant answers.

Journal and Congress Suggester

Journal and Congress Suggester agent automates this task, using deep analysis of manuscript content, journal metadata, and author preferences, offering ranked, personalized recommendations.

Plain Language Generation

Plain Language Generation agent automates summary drafting, securely transforming clinical trial and publication data into accessible, patient-friendly versions, while retaining scientific rigor.

Learn how we can optimize your organization’s Scientific and Medical Affairs Programs with ARIN

Latest Resources

Insights

June 19, 2025

Conquering the Challenges of Scientific Publications with Automated Solutions

Success Stories

Feb 27, 2025

Launching a Global Medical Information System for a BioPharma Company that specializes in Rare Diseases

Announcements

November 14, 2023

JAMP Pharma Group Chooses SciMax Global as Their Medical Information Provider

Events & Webinars

May 2, 2025

Medical Affairs Professional Society EMEA 2025, 12-14 May 2025, London