How is ScrapeOps different from a normal web scraper?

A scraper fetches one site at a time and breaks often. ScrapeOps fans a single query across 20+ connectors, deduplicates the results, and returns clean, model-ready text with provenance on every page.

Which data sources does ScrapeOps cover?

General web and spider crawls, file extraction (PDF, Excel, CSV, DOCX), social platforms, news, and India-specific sources including MCA21, BSE/NSE, SEBI, and RBI, plus SEC EDGAR for global filings.

Can ScrapeOps feed a RAG pipeline?

Yes. Output is deduplicated, comprehension-ready text with source attribution, which is exactly what retrieval-augmented generation and agent systems need to stay accurate and current.

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READINGRECEIVED · STAND BY82 8B BB A1 E9 27IDENTITY SUPPRESSEDA3 46 1E 39 0C 9654 3C 47 F8 0F ED0C 3B A2 DA F3 A9TIMESTAMP: CLASSIFIED01 7D BC 99 9F CAPRE-RELEASE08 28 E6 F1 E7 3ESTANDING BY38 5B 8F 1C C5 B2BLACKOUT ACTIVEPRE-RELEASE34 E4 EF 01 E3 FDIDENTITY SUPPRESSEDLINE 01 — ENCRYPTED6C 25 16 FC EA 8E66 6D D1 32 C9 F6STANDING BYINTERNAL CIRCULATION ONLYPRE-RELEASE9B 4F B4 01 38 32C4 73 3E BB 9B 07AWAITING CLEARANCE71 BA 0A 5B B0 4CMARK — D · LC9 80 72 F7 B2 AB50 17 B6 EC 6B 106C 44 CF 2C B8 09C7 4D 57 23 73 5F77 49 C2 36 B6 21BURN AFTER READING67 94 77 2F A9 5A16 D1 77 E2 E1 C2F6 5C 7C 25 6A 353E 4B 24 23 8D BDB7 40 5B DD BB DABURN AFTER READING4C 54 77 63 1A 31D6 AA 08 67 63 3BEC 6C 36 24 14 C03B 38 88 49 A8 8FPRE-RELEASETIMESTAMP: CLASSIFIED8D C4 7D 7E 79 1F16 93 2F 14 4E 07HANDLER: UNKNOWN42 39 46 9D 2D AEMARK — D · LSIGNAL NOMINAL70 A6 AE CF D0 9125 B2 32 72 45 6125 C1 9B E0 4D 579A 88 1C 1C BB 19DEKRYPT LABSSTANDING BYSTANDING BYASSET UNCONFIRMEDD7 35 12 69 51 3ACHANNEL ENCRYPTEDCOMPARTMENTALIZEDTRANSMISSION SECUREDB8 4F 3F 6C 98 0CEXTRACTION PENDINGIDENTITY SUPPRESSEDD4 92 91 CD 99 67AE 9D 6E 95 1C 57MEMORY WIPE PENDING82 BA CA 83 91 83BURN AFTER READINGNOTHING TO ANNOUNCEEE 77 84 04 43 4ELINE 01 — ENCRYPTED52 6F D5 63 D9 0DNODE: OFFLINESTANDING BYC7 0B 38 35 67 D584 D8 83 1F EE 0141 AF 93 F6 20 7FSTANDING BYFC F6 94 2B 3A 65ASSET UNCONFIRMED7D DA A7 62 CF CDC5 78 C1 D0 67 B732 95 C8 5A A0 BED3 FF 22 9D C5 B5AE 45 2F 29 E0 32NODE: OFFLINE5A A8 F9 4A 35 FCBD 4D A5 A2 06 98B8 B5 1C AC FE 4BOBSERVER 04 · ENGAGEDNODE: OFFLINE16 D0 32 B6 89 ECSTAGE 00 CONSTRUCTIONORIGIN: REDACTEDAA E2 35 BF 09 DFTIMESTAMP: CLASSIFIEDDEKRYPT LABSDEKRYPT LABSBLACKOUT ACTIVEZERO FOOTPRINTSTAGE 00 CONSTRUCTION1C ED D3 4E 5B D6DEKRYPT LABSDA A7 D5 4E 75 50OPERATION · UNDISCLOSEDSTANDING BYDC 50 A4 58 B7 F7C0 B4 B2 D3 A0 01OPERATION · UNDISCLOSEDMARK — D · LSIGNAL NOMINALPROTOCOL: DARK6F 70 66 E3 F7 0BAWAITING CLEARANCEFC 0C 49 7B E2 051B 08 AB B0 D5 F40A F6 FB 7A 1E F5F2 17 A1 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◇ Products · ScrapeOps

ScrapeOps — Data Acquisition Engine

● ACTIVE

Turn one query into hundreds of deduplicated, comprehension-ready sources — the data layer that keeps AI systems from breaking on missing or stale information.

Put ScrapeOps on your data problem →

◇ The problem

AI systems don't fail on reasoning — they fail on data. The sources are scattered, duplicated, blocked, or out of date, and your pipeline inherits every gap.

◇ What ScrapeOps does

ScrapeOps is a Data Acquisition Engine. One query fans out across the web, filings, news, social, and structured registries, then comes back as hundreds of relevant, deduplicated, comprehension-ready sources.

It solves the "where's the data" problem that quietly breaks most RAG and agent systems. Instead of stitching together brittle scrapers, you get a single clean feed your models can actually read.

Twenty-plus connectors span general web and spider crawls, file extraction (PDF, Excel, CSV, DOCX), social platforms, news, and India-specific sources like MCA21, BSE/NSE, SEBI, and RBI.

◇ Capabilities

One query, hundreds of sources

Fan out across web, files, social, news, and registries in a single call.

Deduplicated and comprehension-ready

Near-duplicates collapsed, boilerplate stripped, text ready for a model to read.

20+ connectors

From general web and spider crawls to MCA21, BSE/NSE, SEBI, RBI, and SEC EDGAR.

File extraction built in

PDF, Excel, CSV, and DOCX parsed to clean text alongside the web results.

Confidence and provenance

Every page carries its source and a confidence signal, so you can trust the feed.

◇ How it works

01Query. Send one query or seed URL and pick the platforms and depth you need.
02Acquire. ScrapeOps fetches across connectors with the right strategy per source.
03Clean. Results are deduplicated and reduced to comprehension-ready text.
04Use. Pull the structured feed straight into your RAG pipeline or model.

◇ Who it's for

AI/ML engineers and RAG builders
Data teams maintaining freshness at scale
AI-product founders shipping on real-world data

◇ Frequently asked

What is ScrapeOps?: ScrapeOps is a data acquisition engine that turns a single query into hundreds of deduplicated, comprehension-ready sources across the web, files, news, social, and registries — built to feed AI and RAG systems.
How is ScrapeOps different from a normal web scraper?: A scraper fetches one site at a time and breaks often. ScrapeOps fans a single query across 20+ connectors, deduplicates the results, and returns clean, model-ready text with provenance on every page.
Which data sources does ScrapeOps cover?: General web and spider crawls, file extraction (PDF, Excel, CSV, DOCX), social platforms, news, and India-specific sources including MCA21, BSE/NSE, SEBI, and RBI, plus SEC EDGAR for global filings.
Can ScrapeOps feed a RAG pipeline?: Yes. Output is deduplicated, comprehension-ready text with source attribution, which is exactly what retrieval-augmented generation and agent systems need to stay accurate and current.

Put ScrapeOps on your data problem →

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