Unstructured Data Processing Pipeline

Extract & Index Unstructured Data from Across Your Organisation

Automatically ingest files from SharePoint, Teams, OneNote, and OneDrive โ€” extract text with Python, chunk, embed, and index for AI-powered semantic search.

Get started free See how it works
4
Source platforms
916+
Chunks indexed
1,536
Vector dimensions
<5 min
Full pipeline run
๐Ÿ“ SharePoint
๐Ÿ’ฌ Microsoft Teams
๐Ÿ““ OneNote
โ˜๏ธ OneDrive
๏ผ‹ More coming

Four platforms. One unified pipeline.

Connect to your Microsoft 365 environment and let the pipeline handle the rest โ€” files of every format, automatically extracted and indexed.

๐Ÿ“

SharePoint

Ingest documents from SharePoint document libraries across any site. Handles all Office formats, PDFs, and embedded attachments with full metadata.

.docx .xlsx .pptx .pdf .xlsm .doc .ppt
๐Ÿ’ฌ

Microsoft Teams

Reads files shared in Teams channels and private chats. Discovers all team sites and libraries via Microsoft Graph API automatically.

Channel Files Team Sites Private Channels
๐Ÿ““

OneNote

Extracts notebook pages as HTML, parses clean text via BeautifulSoup, and processes any Office attachments embedded in notes.

Notebooks Sections Pages (HTML) Attachments
โ˜๏ธ

OneDrive

Connects to personal and shared OneDrive drives. Crawls folders recursively and processes all supported document types.

Personal Drive Shared Drives Nested Folders
โœ“ Live

Every unstructured format, handled natively

Python-based extraction โ€” no external OCR service required. Each format has a dedicated extractor.

๐Ÿ“„ PDF pypdf
๐Ÿ“ Word (.docx) python-docx
๐Ÿ“Š Excel (.xlsx/.xls) openpyxl
๐Ÿ“ฝ๏ธ PowerPoint (.pptx) python-pptx
๐Ÿ““ OneNote HTML BeautifulSoup
๐Ÿ“‹ CSV csv module
๐Ÿ”ง JSON json module
๐Ÿ“ƒ Plain Text / Markdown utf-8 decode
๐Ÿงฎ Macro Excel (.xlsm) openpyxl + strip VBA

From raw file to searchable knowledge in minutes

A fully automated pipeline โ€” ingest, extract, chunk, embed, and index โ€” with no manual steps.

Step 01
๐Ÿ“ฅ

Ingest

Microsoft Graph API pulls files from SharePoint, Teams, OneNote, and OneDrive into Azure Data Lake Storage Gen2 with full provenance metadata.

Step 02
๐Ÿ

Python Extraction

Python-native extractors parse every file type โ€” pypdf for PDFs, python-docx for Word, openpyxl for Excel, BeautifulSoup for OneNote HTML. No external OCR service needed.

Step 03
โœ‚๏ธ

Chunk & Embed

Extracted text is split into semantic chunks with full provenance metadata. Each chunk is embedded using Azure OpenAI (1,536-dim vectors).

Step 04
โšก

Index & Search

Chunks are pushed to Azure AI Search with hybrid BM25 + vector search and semantic re-ranking for best-in-class retrieval accuracy.

Everything you need for enterprise document intelligence

Built on Python and Azure with a fully configurable processing pipeline โ€” no proprietary extraction service lock-in.

๐Ÿ

Python-Only Extraction

All file parsing uses pure Python libraries (pypdf, python-docx, python-pptx, openpyxl, BeautifulSoup). Fast, cost-free, and fully portable โ€” no Azure DI dependency.

๐Ÿง 

Semantic + Vector Search

Hybrid BM25 full-text search combined with 1,536-dim vector embeddings and Azure AI semantic re-ranking for highly accurate retrieval.

๐Ÿ“Ž

Attachment Processing

Automatically extracts and indexes files embedded inside Word, Excel, and PowerPoint documents alongside their parent with full lineage tracking.

๐Ÿ”„

Incremental Updates

Smart deduplication via content hashes ensures only new or changed files are re-processed, keeping costs low and the index fresh.

๐Ÿ—บ๏ธ

Rich Provenance Metadata

Every chunk carries source platform, site, library, file path, page number, chunk index, block type, modification dates, and more.

๐Ÿ”’

Enterprise Security

All data stays within your Azure tenant. Managed identity auth, ADLS Gen2 encryption at rest, and role-based access throughout.

Enterprise-grade infrastructure, Python-first extraction

Managed Azure services for storage, search, and embeddings โ€” open-source Python for all document parsing.

Storage
Azure Data Lake Storage Gen2
PDF Extraction
pypdf (Python)
Word / PowerPoint
python-docx ยท python-pptx
Excel
openpyxl (sheets + tables)
HTML (OneNote)
BeautifulSoup4
Embeddings
Azure OpenAI text-embedding-3-small
Search
Azure AI Search (Hybrid + Semantic)
Ingest Sources
Microsoft Graph API
Pipeline Runtime
Python ยท Azure Functions
Vector Dimensions
1,536-dim HNSW Index
Chunking
Hybrid chunker ยท tiktoken
Portal
Laravel 12 ยท Blade ยท Tailwind CSS

Ready to unlock your unstructured data?

Connect your Microsoft 365 tenant and have your first documents extracted, chunked, and indexed in minutes.

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