Data Extraction & Scraping Services in India

Overview

Your business depends on data that is trapped in formats nobody designed to be read by a machine: dense PDFs, scanned invoices, complex websites, contracts written in Word and printed to paper twenty years ago.

FoundrySoft is a data extraction company in India building the pipelines that get that data out. Not a demo that works on five clean samples: a production pipeline with validation, monitoring, and a known error rate that you can point at ten thousand documents and trust.

The part most extraction projects get wrong

Nearly every extraction project succeeds on the pilot and fails at scale, and it usually fails the same way.

The pilot uses ten clean documents. Production has a scanned fax from 1998, a table that breaks across three pages, a supplier who changed their invoice template last quarter, and a Portuguese-language variant nobody mentioned. The model does not error on these; it returns something confident and wrong. Without validation, that wrongness lands in your database and is discovered months later by an accountant.

So the engineering that matters is not the extraction call. It is everything wrapped around it:

• A schema with teeth. We define the output shape up front and validate every field against it. A date that isn't a date, a total that doesn't equal the sum of line items, and a required field that came back empty are all caught before the record is written, not after.
• Confidence routing. Every extracted record carries a confidence signal. High-confidence records flow straight through. Anything ambiguous routes to a human review queue with the source document and the specific uncertain field highlighted. You decide the threshold; the pipeline enforces it.
• A regression suite for documents. We keep a corpus of your genuinely hard documents and re-run it whenever a prompt, model, or parser changes. This is the single practice that most separates extraction pipelines that survive from ones that quietly degrade.

Our core data extraction services

AI-powered document extraction (OCR + vision models)

Legacy OCR reads characters but not structure: it will happily turn a table into a wall of text. Vision-capable models read the document the way a person does, which is what makes multi-page tables, handwritten annotations, and inconsistent layouts tractable.

We build these pipelines on current frontier models, typically Claude Opus 5 or Claude Sonnet 5 depending on the accuracy-to-cost profile the volume demands, and we tell you which one your workload actually needs rather than defaulting to the most expensive option. High-volume, low-ambiguity classification steps often run on a smaller model, with the expensive model reserved for the documents that genuinely need it. On a large corpus that routing decision is usually the difference between a viable unit cost and an unviable one.

Typical work: invoices and purchase orders, medical records, insurance claims, legal contracts, bills of lading, bank statements, and the long tail of forms specific to your industry.

Advanced web scraping

We build scrapers that keep working after the target site redesigns. That means resilient selection strategies rather than brittle CSS paths, headless browsers for JavaScript-rendered content, proper request pacing, proxy rotation where the terms of service permit it, and alerting the moment extraction volume drops below expectation, because the failure mode of a scraper is rarely a crash. It is silently returning empty.

We will also tell you when scraping is the wrong answer. If the data is available through an API, a bulk export, or a licensing agreement, that path is cheaper and more durable than anything we could build, and we would rather say so at the scoping call than six months in.

Unstructured text parsing and enrichment

Support tickets, product reviews, call transcripts, and email archives contain answers to questions your BI tools cannot ask. We build NLP pipelines that extract entities, classify by theme, score sentiment, and land the result in your warehouse as queryable columns.

Compliance and data handling

Extraction work usually touches sensitive material, so this is settled before code is written, not after. We work under NDA from the first call. We can run the entire pipeline inside your cloud account, so your documents never transit our infrastructure. For workloads under GDPR, HIPAA, or India's DPDP Act, we scope the data-residency and retention requirements into the architecture rather than retrofitting them. Where a project involves personal data, we build in PII detection and redaction at the ingestion boundary.

What working with us looks like

You get senior engineers in Chennai with substantial daily overlap with US business hours, a fixed scope with a fixed quote before we start, and complete ownership of the source code, the prompts, the eval suite, and the extracted data. There is no proprietary runtime you have to keep paying us to operate. If you want to take the pipeline in-house after handover, everything you need to do that is in the repository.

Related reading from our engineering team: semantic search with embeddings and Qdrant covers making extracted data searchable, and automating legacy systems without an API covers the case where the data lives behind a UI with no integration path at all.

Stop paying people to copy and paste. Let's scope the pipeline.