Cuckoo.ai - Agentic AI for Rapid Pharmaceutical Opportunity Assessment

Proof of Concept demonstrating an AI-powered system for accelerating pharmaceutical R&D decisions

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Problem Statement

Pharmaceutical companies lose significant time and resources due to repeated, manual evaluations of drug opportunities:

Metric	Current State
Evaluation Time	8-12 weeks per molecule
Cost per Evaluation	$38K-$52K
Rework Rate	~35% (no institutional memory)
Data Sources	6+ disconnected systems

The industry is entering a $236B patent cliff (2025-2030) — companies must find differentiated opportunities faster or lose market share.

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Our Solution

An Agentic AI System with Institutional Knowledge Memory that:

• ✅ Reduces evaluation time from 8-12 weeks to 5-10 days (~87% faster)
• ✅ Triples annual evaluation throughput (10-12 → 24-36 evaluations/year)
• ✅ Eliminates redundant research through institutional memory (<5% rework vs 35%)
• ✅ Delivers standardized, auditable reports with confidence scores

Key Innovation: Read-Before-Write Logic

Unlike traditional AI assistants, our system checks institutional memory first before conducting new research.

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Quick Start

# Install dependencies
pip install -r requirements.txt

# Run demo (command line)
python demo_run.py

# OR launch web interface
streamlit run app.py

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Team

Name	Role
Pranav Taneja	Prompt Engineering
Sanket Wathore	Deep Learning & Healthcare Analytics
Sneha Yadav	Data Preparation & Visualization
Gudaru Pragathi	Data Management
Vybhav Chaturvedi	Solution Architect

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