Content Quality Dashboard & AI-Powered Audit Platform
Identified the absence of a systematic content quality measurement system and led the initiative to design and build Tata 1mg's AI-driven content quality platform from scratch.
The platform validates clinical content and regulatory classifications against source references, identifies gaps, and recommends corrections at scale for ePharma and eDiagnostics.
Combines automated audits, prompt-based evaluation workflows, and human review.
The Challenge
- No standardised benchmark existed to measure the quality of drug content on the platform, and quality was assessed subjectively.
- Manual audits of thousands of drug pages were unsustainable at scale without automation.
- Establishing consensus on what 'good' looks like across clinical accuracy, regulatory compliance, SEO value, and user readability simultaneously.
The Approach & Solution
- Defined a multi-dimensional scoring framework with weighted attributes across Comprehensiveness, Accuracy, and Consumability.
- Built an audit pipeline using Python for bulk content extraction and evaluation, with Flesch-Kincaid integrated for readability assessment.
- Deployed AI-assisted prompt-based evaluation workflows to scale audit capacity — enabling assessment of 500+ drugs per audit cycle.
- Benchmarked content against international competitor platforms.
Key Results & Commercial Impact
Technology Stack & Tools
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