We extract NPA property listings, e-auction notices, reserve prices, and EMD deadlines from findauction.in. Delivered as clean JSON, CSV, or Parquet to S3 or PostgreSQL on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from findauction.in. All fields typed and schema-versioned.
"property_id": "FA-98231", "title": "3 BHK Flat in Andheri West", "category": "Residential", "city": "Mumbai", "borrower_name": "Rahul Sharma", "institution_name": "State Bank of India", "possession_type": "Symbolic"
| # | property_id | title | category | city | state | borrower_name |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Auction Details objects from findauction.in. All fields typed and schema-versioned.
"auction_id": "AUC-5512", "reserve_price": 14500000, "emd_amount": 1450000, "emd_submission_date": "2026-08-14", "auction_date": "2026-08-16", "tender_fee": 5000
| # | auction_id | property_id | reserve_price | emd_amount | emd_submission_date | auction_date |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Bank & Contact Info objects from findauction.in. All fields typed and schema-versioned.
"bank_name": "HDFC Bank", "branch_name": "Koramangala Branch", "authorised_officer": "Vikram Desai", "contact_number": "+91-9876543210", "email_address": "recovery.blr@hdfc.com", "ifsc_code": "HDFC0000123"
| # | institution_id | bank_name | branch_name | authorised_officer | contact_number | email_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Legal & Notice Data objects from findauction.in. All fields typed and schema-versioned.
"notice_id": "NOT-9912", "sarfaesi_act_flag": true, "notice_type": "E-Auction Sale Notice", "publication_date": "2026-07-20", "newspaper_name": "Times of India", "notice_url": "https://findauction.in/notice/9912"
| # | notice_id | property_id | sarfaesi_act_flag | notice_type | publication_date | newspaper_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Location & Geography objects from findauction.in. All fields typed and schema-versioned.
"address_raw": "Flat No 402, 4th Floor, Skyline Apts", "locality": "Andheri West", "district": "Mumbai Suburban", "pincode": "400053", "latitude": 19.1363, "longitude": 72.8276
| # | property_id | address_raw | locality | district | pincode | city_tier |
|---|---|---|---|---|---|---|
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Our Findauction scraper handles every layer of the platform: property metadata, reserve pricing, EMD deadlines, and bank contact details. We normalise inconsistent location data and parse unstructured notice text.
Title, carpet area, possession type, and borrower names extracted per listing with asset category mapping.
Capture reserve prices, Earnest Money Deposit amounts, tender fees, and exact submission deadlines.
Extract institution names, specific branch locations, IFSC codes, and authorised officer contact details.
Flag properties explicitly listed under the SARFAESI Act, including publication dates and newspaper sources.
Track exact e-auction start and end dates to build accurate bidding calendars.
Standardise localities, districts, and pincodes from raw address strings for geospatial analysis.
Capture direct links to attached physical notices and bank tender documents.
Target specific cities, property types, or bank names using programmatic filter execution.
Run continuous pipelines at daily cadences to capture new listings and modified auction dates.
Brief in. Clean data out.
Provide target cities, bank names, or property categories. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and text parsing modules for findauction.in.
Schema validation, null-rate checks, and reserve price outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or PostgreSQL database on agreed cadence.
Bank auction data is notoriously unstructured. Here is how we ensure data quality and pipeline resilience.
Property aggregators implement strict rate limits. Our crawlers use residential ISP proxies with randomised request timing to maintain continuous extraction without IP bans.
Bank auction notices often contain raw text blocks instead of clean fields. We use regex and text parsing to extract carpet area, borrower names, and possession types accurately.
Findauction search results require stateful sessions to traverse deep pagination. We maintain cookie integrity to ensure zero data loss across thousands of result pages.
Banks upload listings with inconsistent spelling for branches and localities. Our pipeline maps these variations against a master directory to ensure clean grouping in your warehouse.
We maintain a hash index of auction dates and EMD deadlines. Subsequent runs only push modifications or newly added properties, reducing your downstream processing load.
Investors track reserve prices against retail market rates to identify undervalued distressed assets.
Real estate platforms syndicate bank auction data to expand their inventory of secondary market properties.
Asset Reconstruction Companies monitor market supply of defaulted properties across specific bank branches.
Law firms track SARFAESI notices to verify property encumbrances before standard market transactions.
Analysts correlate auction reserve prices with retail property prices to map distressed asset discounts per city.
Funds configure alerts for commercial properties exceeding specific carpet area thresholds in Tier 1 cities.
"Bank auction notices are fragmented across thousands of branches and PDFs. Findauction aggregates them, but extracting that data requires a structured pipeline."
Extracting NPA and SARFAESI property data requires parsing inconsistent bank formats, handling complex pagination, and standardising location strings across India. DataFlirt manages this extraction pipeline so your analysts can focus on asset valuation, not DOM parsing or PDF OCR.
Everything supported by our findauction.in scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright manages JavaScript rendering and stateful pagination flows.
We maintain pools of residential ISP proxies for the IN region. Rotation happens per-request to bypass rate limits.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About findauction.in scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under Indian law. SARFAESI notices and bank auction details are legally required to be in the public domain. DataFlirt extracts only public property and auction metadata. We do not bypass authentication walls for private bidding portals.
We use residential ISP proxies, realistic browser fingerprints, and request timing modelled on human behaviour. This prevents rate limiting and IP bans during large-scale extraction.
Yes. While findauction.in digitises most fields, our pipeline can include OCR modules to extract specific text from attached physical newspaper publication PDFs if required.
We typically configure daily crawls to capture new property listings and modifications to EMD deadlines or auction dates. Real-time streaming is available for specific search parameters.
Yes. We map raw string inputs against a master directory of Indian financial institutions to ensure clean grouping and filtering in your database.
Our smallest packages start at tracking specific tier-1 cities or specific banking institutions with weekly delivery. Contact us with your target scope for exact pricing.
Absolutely. We provide a sample run of up to 100 property listings as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of active listings or a continuous feed of new SARFAESI notices, we scope, build, and operate the pipeline. Tell us what you need.
