AI-Powered Content Ingestion™ for Scientific Research Data
Unlock insights hidden deep within scientific documents automatically.
Scientific research generates a vast and diverse set of digital assets: from journal articles and research papers to email threads and institutional reports. 80% of all data is trapped in unstructured formats making it difficult and time consuming to unlock it for use.
AI-Powered Content Ingestion™
brings automation to this challenge.
Designed to operate at scale, it ingests large batches of digitized research materials and uses advanced language models to extract, summarize, and structure key information with or without human intervention.
Key Features
Automated Batch Processing
Upload millions of assets from PDFs to emails, and receive structured, summarized output tailored to your needs.
Human-in-the-Loop Dashboard
A user-friendly interface allows for real-time search, audit, and targeted review of processed content.
Customizable Prompts
Use custom instructions to define what AI should extract, summarize, or highlight, enabling domain-specific flexibility.
Scalable
and Secure
Hosted in a secure cloud environment from small-scale tests to full-scale research pipelines.
Ideal for
01
Pharmaceutical and Biotech Research Teams
02
Academic Labs and University Research Groups
03
Digital Library and Journal Platforms
04
Government and Regulatory Science Bodies
05
Corporate R&D and Competitive Intelligence Teams
By transforming unstructured research documents into structured, searchable intelligence, our AI-powered Content Ingestion accelerates discovery, improves accuracy, and enables powerful data-driven insight.
Case Study: Building a Scalable Research Intelligence Business
The Client
A data-focused scientific data and research aggregator creating a proprietary scientific research catalog for the life sciences sector.
The Challenge
The client aimed to build a subscription platform that aggregates and enriches scientific content from thousands of sources, including peer-reviewed journals, institutional repositories, and internal white papers. However, the diversity in document structure and file types made large-scale ingestion and standardization an overwhelming manual task. They needed a way to rapidly process incoming data and surface valuable insights to their end users.
The Solution:
AI Powered Content Ingestion™
We integrated AI Document Automation Pro™ into their ingestion pipeline. Using batch processing and customizable prompts, they automated the extraction of key data points such as:
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Research objectives and conclusions
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Entity recognition, e.g., compounds, gene markers, diseases
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Study types and methodologies
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Publication metadata
Processed outputs were structured into a format that could be easily indexed and fed into the client's proprietary research catalog interface. The platform's UI allowed analysts to review and fine-tune system parameters over time, continuously improving extraction accuracy.
The Results
By automating the most labor-intensive part of their content pipeline, the client was able to increase the value of their solution to their customers.
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90% reduction in manual document review time
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Over 1 million documents processed in 6 months
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Accelerated time-to-market for content ingestion
