Transform lecture chaos into learning clarity—automatically.
Students face a torrent of 60–90 minute lecture videos per course—dozens weekly—burying concepts, examples, deadlines, and action items in unstructured speech, creating massive backlogs where rewatching one thing means hours lost and critical instructions of skipped part forever missed. This creates a systemic bottleneck:
- Knowledge exists, but is not addressable
- Deadlines exist, but are not structured
- Questions repeat, because answers are not retrievable
- Learning quality depends on manual effort, not scalability
ORCHESTRIX LECTURE is an AI-driven orchestration system that transforms unstructured lecture media into a structured, queryable, and actionable learning layer.
The platform ingests raw lecture videos and autonomously:
- Generates timestamped, speaker-aware transcripts
- Segments lectures into semantically coherent topic blocks
- Synthesizes study-ready artifacts (summaries, flashcards, practice questions)
- Extracts high-confidence action items and deadlines and syncs them with calendars
- Powers retrieval-based Q&A, reducing repetitive student queries
By converting lectures from passive recordings into addressable knowledge units, Orchestrix Lecture eliminates redundant manual work, prevents missed deadlines, and enables scalable, personalized learning !!!.
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End-to-end Video → Knowledge
Automated transcription with timestamps and topic-wise structured outputs. -
High-quality Content Synthesis
Concise summaries, hierarchical notes, flashcards, and practice questions per lecture segment. -
Action Item & Deadline Extraction
Detects tasks and due dates from spoken instructions with confidence scoring. -
Semantic Retrieval & Q&A
Vector-based semantic search with RAG-enabled contextual Q&A and source attribution. -
Personalized Learning Delivery
Adaptive difficulty levels and automated weekly study digests via email. -
Scalable Batch Processing
Parallel processing for bulk lecture ingestion with configurable model selection. -
Integrations
Google Calendar sync, SMTP/Gmail notifications, and LMS-ready exports (CSV/JSON).
| Layer | Technologies |
|---|---|
| Orchestration | FastAPI, Uvicorn, CrewAI |
| AI Engine | Google Gemini, OpenAI Whisper, LangChain |
| Storage | MongoDB, ChromaDB (Vector DB) |
| ML/NLP | PyTorch, Sentence Transformers |
| Integrations | Google Calendar API, Gmail SMTP |
| Infrastructure | Python 3.10+, asyncio, Pydantic |
Python 3.10+
MongoDB (local or Atlas)
Google Cloud API credentials
SMTP-enabled email account1️⃣ Clone & Setup Environment
git clone https://github.com/AjayChikate/Orchestrix-Lecture.git
cd orchestrix-lecture
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate2️⃣ Install Dependencies
# Backend dependencies
pip install -r Backend/requirements.txt
# Agent dependencies
pip install -r Agents/requirements.txt3️⃣ Launch Backend
cd Backend
python main.pyBefore ORCHESTRIX LECTURE:
- ⏰ 4-6 hours manual content prep per lecture
- 📉 Most of students miss critical deadlines
- 🔁 Instructor answers same questions 50+ times
- 🔍 Forgot what was taught, what to revise
After ORCHESTRIX LECTURE:
- ⚡ <10 minutes automated processing
- ✅ No more “where was that deadline?” moments.
- 🤖 Reduction in repetitive Q&A load
- ⚡ Delivers weekly personalized email digests aggregating key concepts, deadlines, and adaptive study recommendations—ensuring students stay informed without information overload.
Contributions are welcome! Please feel free to submit a Pull Request.
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