The Hidden Cost of Patchwork Data Systems

Modern AI and analytics need data that lives outside your transactional systems: competitor pricing, public regulatory filings, market and economic signals, news and social content, customer review and forum content, and the long tail of unstructured internal documents, including PDFs, contracts, and transcripts scattered across departments. Bringing this data in reliably, at scale, and with Read More...

What Is Harvest?

Harvest is Bandhan Technologies' enterprise data acquisition and indexing accelerator. It combines scalable, observability-instrumented data scrapers and ingestion pipelines; structured extraction and entity recognition; OneLake-native landing and indexing; and governance and lineage practices engineered for both external and internal data sources. Read More...

How Harvest Works

Harvest is built on a managed, observable data acquisition and indexing architecture engineered for enterprise reliability.

Step 1

Step 2

Step 3

Step 4

Step 5

Source Configuration

Declarative configuration of external sources, including websites, APIs, and document repositories, alongside internal document stores.

Scrape and Ingest

Scalable, observability-instrumented scrapers and ingestion pipelines with anti-bot, rate, and schema-change handling.

Structured Extraction

Entity recognition, table extraction, and semantic structuring of unstructured content, including PDFs, articles, and transcripts.

Indexing and Landing

Native landing in OneLake with vector embeddings, full-text index, and lineage metadata.

Governance and Consumption

Data products available to AI and analytics consumers with quality, lineage, and freshness service level agreements.

What Harvest Handles

Resilient Web Scraping

Production-grade scrapers with anti-bot handling, schema-change detection, and automated remediation, built for source volatility.

Document and PDF Indexing

Large-scale ingestion and structured extraction from PDFs, contracts, transcripts, and operational documents.

Entity and Table Extraction

Semantic structuring of unstructured content with entities, tables, and relationships extracted for downstream consumption.

OneLake-Native Landing

Data lands directly in OneLake with vector embeddings, full-text indexing, and lineage metadata.

Source Quality Monitoring

Observability and alerting on source freshness, schema drift, and quality anomalies.

Governed Data Products

Acquired data exposed as governed data products with quality service level agreements and consumption documentation.

External Data You Can Actually Depend On

Reliable external data supply

Scrapers and ingestion pipelines that hold up in production, not just in development

Faster AI use-case enablement

Acquired data is AI-consumable from day one, with no per-project data engineering required

Unlocked internal document value

PDFs, contracts, and documents become first-class AI and analytics data sources

Reduced data engineering toil

Centralized acquisition replaces team-by-team scraper maintenance

Audit-ready data lineage

Every record traces back to source, time, and method, supporting compliance and review

Operational visibility

Source health, freshness, and quality are monitored and alerted continuously

The Sources Harvest Brings In

Competitive Pricing and Market Intelligence

Continuous acquisition of competitor pricing, assortment, and positioning signals from public sources.

Regulatory and Public Filings Ingestion

Scheduled ingestion of regulatory filings, court records, and public registry data for compliance and intelligence.

Customer Review and Voice-of-Customer Aggregation

Aggregate customer reviews, forum content, and social signals from public sources for sentiment and trend analysis.

Internal Document AI Enablement

Index contracts, policies, manuals, and historical correspondence for AI-grounded enterprise applications.

Alternative Data for BFSI and Investment

Structured acquisition of alternative data sources for risk, investment, and intelligence applications.

What Sets Harvest Apart

Proven in Practice

Harvest is operated by Bandhan Technologies' data engineering practice, combining senior engineers with deep experience in large-scale web acquisition, document indexing, and Azure data architecture. Read More...

Ready to Make External and Unstructured Data a Reliable Supply, Not a Recurring Scramble?

Book a Harvest pilot scoping call with a Bandhan data engineering specialist. We will review your priority data sources, whether external or internal, and define a pilot that demonstrates reliable acquisition, indexing, and AI-consumable delivery.