Logo
  • Cases & Projects
  • Developers
  • Contact
Sign InSign Up

© Copyright 2025 Many.Dev. All Rights Reserved.

Product
  • Cases & Projects
  • Developers
About
  • Contact
Legal
  • Terms of Service
  • Privacy Policy
  • Cookie Policy
AI-Powered Chemical Identification and Property Retrieval System
  1. case
  2. AI-Powered Chemical Identification and Property Retrieval System

This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

AI-Powered Chemical Identification and Property Retrieval System

netguru.com
Health & Fitness
Pharmaceuticals
Life Science
Electronics

Inefficient Chemical Identification Process

Merck's manual chemical identification process, relying on domain experts to analyze scientific literature, was excessively time-consuming (6 months) and resource-intensive. This bottleneck hindered the timely identification of key chemical compounds for future sales initiatives and slowed down R&D activities. The manual process also required significant effort from domain experts, diverting them from other critical tasks.

About the Client

A multinational science and technology company focused on healthcare, life science, and electronics, operating globally with a significant chemical research and development division.

Project Goals

  • Reduce the time required for chemical identification from literature review.
  • Automate the extraction of chemical compounds and their properties from scientific literature.
  • Improve the accuracy and efficiency of chemical information retrieval.
  • Enable faster identification of existing Merck products to avoid redundant research.
  • Enhance the productivity of domain experts by automating routine tasks.

System Functionality

  • PDF upload and processing.
  • AI-powered chemical compound extraction.
  • Chemical property retrieval (InChIKey, SMILES, Molecular Formula, CAS Number, Synonyms).
  • Cross-reference with Merck's internal catalog database.
  • Display of chemical information and 2D structure.
  • Integration with existing Merck systems (Catalog DB, AWS infrastructure, GPT service).

Preferred Technologies

Large Language Models (LLMs) - Azure OpenAI
LangChain (LLM framework)
Chemical Databases (e.g., PubChem, ChemSpider)
AWS Infrastructure
GPT Service (Merck's internal)

Required Integrations

  • Merck Catalog Database
  • AWS Security Infrastructure
  • Merck's Internal GPT Service

Non-Functional Requirements

  • Scalability to handle large volumes of scientific literature.
  • High performance and low latency for rapid chemical identification.
  • Enterprise-level security and compliance.
  • Accuracy and reliability of chemical information retrieval.
  • Maintainability and extensibility for future enhancements.

Expected Business Impact

The implementation of this system is expected to significantly reduce the time and cost associated with chemical identification, freeing up domain experts to focus on higher-value tasks. The faster identification of chemical compounds will accelerate R&D efforts, potentially leading to new product development and improved sales opportunities. The automation will improve data accuracy and consistency, and enhance overall operational efficiency. The project is projected to reduce chemical identification time from 6 months to approximately 6 hours, resulting in a substantial productivity gain.

More from this Company

Development of a Scalable Home Cleaning Service Platform with Multi-Sided Marketplace Functionality
AI-Powered Teacher Guide Automation Platform
Development of a Trust-Based Digital Ebook Distribution Platform with Pay-What-You-Want Model
Patient-Doctor Communication Platform Expansion and MVP Development
Enhancement of Meal Ordering Web Application for Subscription-Based Meal Delivery Service