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Open-Science Knowledge Visualization for Academia

EdTech/Research – Knowledge Management & RAG

SaaS platform for knowledge mapping in academic research: literature review automation, centralized documentation, interactive visualizations.

-70%

Literature Review Time

+60%

Research Efficiency

1000+

Academic Users

98%

Automation Coverage

Knowledge Management Impact

Advanced AI agents for academic research and knowledge structuring

Project Details

Client

Weeki.io

Sector

EdTech/Research – Knowledge Management & RAG

Year

2020–2023

Key Technologies

PyTorchLangChainNeo4jElasticsearch

Mission

Senior Lead Data Scientist – Knowledge Management & RAG

AI Agent & MLOps

Founder experience / Paris, France

Development of AI agents: integrating vector embeddings and auto-encoders to structure multi-level knowledge maps. LLM + RAG integration: contextualized responses (+ attention weights based on transformer). Workflow automation: ingestion, processing and enrichment via DAGs automation.

Contexte & Environnement

Weeki.io was developing a knowledge-first SaaS platform dedicated to data, R&D and product teams. The complexity of heterogeneous sources (PDFs, videos, code extracts, scientific databases) combined with multi-agent collaborative environments required advanced AI agents for knowledge structuring.

Team

Founder experience / Senior Lead Data Scientist

Environment

PyTorch with Neo4j (graphs), Elasticsearch (vector search), Airflow/N8N orchestration

Objectifs Cles

1Vector embeddings and auto-encoders for multi-level knowledge map structuring

2LLM + RAG integration with transformer-based attention weights for contextualized responses

3Complete workflow automation via DAGs (Airflow, N8N) with 98% automation coverage

4-70% literature review time and +60% research efficiency for 1000+ academic users

5Multi-agent collaborative environment with specialized agents deployed via API, UI, or messaging

Technologies & Infrastructure

PythonPyTorchPyTorch LightningLangChainHugging FaceNeo4jElasticsearchMLflowGitHub ActionsDockerAirflowN8N

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