Sokrateque.ai

Sokrateque.ai is an AI-powered personal research assistant tailored for Master’s and PhD students. It leverages cutting-edge Retrieval-Augmented Generation (RAG) techniques and the OpenAI API to answer users' research-related questions by intelligently utilizing their uploaded research papers, articles, and supplemental data from the web.Students often struggle to manage and retrieve information from vast amounts of academic material. Sokrateque.ai addresses this challenge by offering an intelligent assistant that understands, extracts, and responds to queries in a research-specific context.

"Xpiderz.com has been instrumental in bringing Sokrateque.ai to life. Their team built advanced multi-agent systems, integrated Power BI with LLMs, and delivered a seamless data exploration pipeline that exceeded our expectations. Their deep understanding of AI, automation, and scalable architectures helped us unlock real value from our product. We’re incredibly satisfied with their work and highly recommend them."

Tjaco Walvis

Founder & CEO

Personalized Research Assistant for Graduate Students

Scope of Work

The Sokrateque.ai project focused on building a highly customized RAG-based system capable of: Ingesting and understanding user-uploaded research documents. Retrieving relevant information dynamically from both a Vector Database and on-the-fly without prior indexing. Seamlessly combining external web knowledge with internal document insights to deliver comprehensive answers.

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Key Deliverables:

Custom RAG architecture for dual-mode operation (Vector DB + Live Extraction)
Advanced data ingestion pipelines (including OCR for non-digital PDFs)
Efficient API development for user interaction and backend processing

Developed Pipelines

A Text Extraction and OCR Pipeline was implemented to handle a variety of academic and research document formats, including PDFs, Word files, and image-based documents. Optical Character Recognition (OCR) was integrated to ensure that scanned documents and image-based academic papers could be accurately processed and converted into searchable text.

A Prompt Engineering Pipeline was developed to generate dynamic, context-aware prompts tailored specifically to research questions. This system ensured that responses were accurate, aligned with the topic, and consistent with academic citation standards.

Additionally, an On-the-Go RAG (Retrieval-Augmented Generation) Pipeline was built to deliver real-time, context-rich answers. This pipeline supported both indexed retrieval through a Weaviate Vector Database and direct, live parsing of documents without prior indexing. It merged internal document content with relevant web data to provide comprehensive and high-quality responses.

Technology Stack

Compute: AWS EC2 for backend processing
Storage: AWS S3 for file uploads and extracted data
Database: MySQL for metadata, Weaviate Vector DB for semantic search
LLM: OpenAI API (GPT Models) for response generation
Backend Stack: FastAPI (Python) for API services
Additional: Node.js services for supporting utilities and asynchronous tasks

Results

Reduced Research Time: Students were able to retrieve accurate answers from thousands of pages in seconds.
Higher Research Efficiency: The dual-mode RAG system ensured that even unindexed documents could be immediately used for queries.
Wider Accessibility: OCR capabilities allowed students to use older, scanned materials as part of their research base.
Scalable Architecture: Built on AWS, the system can seamlessly handle increasing user loads and data volumes.

Conclusion

Through a deep integration of RAG methodologies, state-of-the-art text processing pipelines, and OpenAI's language capabilities, Sokrateque.ai sets a new standard for AI-driven research support. It empowers graduate students to spend less time searching — and more time thinking, writing, and innovating.

Industry

Education

Sokrateque.ai was built specifically for the education sector, with a strong focus on assisting graduate-level researchers. Key considerations included: Handling complex academic language and citations. Supporting multiple formats and types of academic papers. Delivering reliable, well-cited, and plagiarism-free AI responses.

Headquarters

Amesterdam, Netherland.

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