29-January-2026
Unlock crucial business data by mastering website anti-scraping. Our 2026 guide covers proven strategies from IP rotation to headless browsers...
Transform Unstructured Web Data into Your Sharpest Competitive Advantage
Raw Data Services
In an era where decisions are only as good as the data behind them, Hir Infotech delivers enterprise-grade raw data services that power smarter strategies across every industry. Since 2013, we have helped 2,745+ businesses across the USA, Europe, and Australia collect, structure, and leverage raw data at scale — with precision, speed, and full compliance. Whether you are a Fortune 500 company, a fast-scaling SaaS platform, or a data-driven mid-market enterprise, our AI-powered raw data pipelines give you the structured, clean, and actionable intelligence you need to outpace competitors and make confident, data-backed decisions.
13+
Years of Expertise
2,745+
Happy Clients
99.2%
Data Accuracy Rate
500+
Data Sources Covered
10M+
Datasets Delivered
Why Raw Data Is the Foundation of Every Intelligent Business Decision
In 2026, raw data is no longer a back-office asset — it is the primary driver of competitive advantage, product development, and revenue growth for B2B organizations globally. Every pricing decision, market entry strategy, sales pipeline, and customer intelligence initiative starts with one critical question: do you have the right data? Hir Infotech specializes in collecting high-volume, structured raw data from thousands of publicly available web sources, directories, and platforms across the USA, UK, Germany, France, the Netherlands, Sweden, Switzerland, Australia, and beyond. Our AI-driven raw data extraction pipelines eliminate manual research bottlenecks, reduce operational costs, and deliver clean, structured datasets that integrate directly into your analytics tools, CRM systems, and AI models — allowing your teams to focus on insight, not collection. With 13+ years of hands-on experience across industries including e-commerce, real estate, finance, healthcare, and logistics, Hir Infotech is the trusted raw data partner for mid-market and enterprise companies that need scale, speed, and reliability.
- Custom Raw Data Extraction: End-to-end collection of unstructured web data from any public-facing source, including e-commerce platforms, business directories, government databases, and industry portals, delivered in your preferred format (JSON, CSV, XML, or direct API feed).
- AI-Powered Data Structuring & Normalization: Our proprietary machine learning pipelines automatically parse, clean, deduplicate, and normalize raw data at scale — ensuring every dataset is analysis-ready and free from noise or inconsistency before delivery.
- Real-Time & Scheduled Raw Data Pipelines: Continuous or interval-based data collection workflows that keep your datasets fresh with real-time updates, daily refreshes, or custom delivery schedules tailored to your operational cadence and use case.
- Compliant Raw Data Collection (GDPR, CCPA, EU AI Act): All raw data collection is governed by a compliance-first framework — covering GDPR for European clients, CCPA for US operations, and the EU AI Act for AI training datasets — so you scale with confidence and zero regulatory risk.
Raw Data at Scale
Hir Infotech’s raw data infrastructure combines AI-driven extraction bots, rotating proxy networks, and intelligent parsing engines to collect structured data from any web source — at any volume, with 99.2% field-level accuracy.
AI-Driven Extraction Engine
Our proprietary AI bots intelligently navigate complex website architectures, JavaScript-rendered pages, and multi-layer pagination to extract 100% of target data fields — eliminating gaps and manual intervention across any source or geography.
Multi-Format Data Delivery
Raw datasets are delivered in your format of choice — CSV, JSON, XML, Excel, SQL, or via direct REST API integration — enabling seamless ingestion into Snowflake, BigQuery, Salesforce, HubSpot, Power BI, and all major enterprise data stacks.
Adaptive Anti-Block Technology
Hir Infotech’s smart proxy rotation, CAPTCHA-handling AI, and browser fingerprint management ensure continuous, uninterrupted raw data collection — even from the most aggressively protected enterprise-grade platforms and e-commerce sites.
Compliance-First Data Governance
Every raw data project is scoped and executed under a documented compliance framework covering GDPR (EU), CCPA (USA), and the 2026 EU AI Act — with data lineage tracking, lawful basis documentation, and full audit trails for enterprise procurement teams.
Trusted by leading brands
High-Value Raw Data Sources and Use Cases for B2B Enterprises
Why Enterprise Teams Are Replacing Manual Data Collection with AI-Powered Raw Data Pipelines
AI-Driven Raw Data Extraction: The Engine Behind Smarter B2B Decision-Making
The old model of manual data research — hiring analysts to copy-paste data from spreadsheets, websites, and PDFs — is fundamentally broken at enterprise scale. It is slow, error-prone, expensive, and impossible to maintain as data volumes grow. In 2026, leading B2B companies across the USA, UK, Germany, France, and the Netherlands are replacing this model with fully automated, AI-driven raw data pipelines that collect, clean, and deliver structured datasets continuously and at any volume. Hir Infotech’s raw data extraction platform processes millions of data points per day using AI agents that intelligently navigate web structures, handle dynamic content, and adapt to source-level changes — without requiring manual reconfiguration. The result is a reliable, always-fresh data infrastructure that integrates directly with your existing BI stack, CRM platform, or AI training environment. Companies that partner with Hir Infotech for raw data services report a 60–80% reduction in time-to-data and a measurable uplift in decision quality across pricing, sales, marketing, and product functions.
Scalable Raw Data Solutions for Every Industry: From Retail to Finance to Healthcare
Structured Raw Data Delivery That Meets Enterprise Compliance and Integration Standards
Not all raw data providers are built for enterprise requirements. Freelancers and generic scraping marketplaces lack the governance, SLAs, and compliance infrastructure that CTOs, CDOs, and procurement leaders demand at scale. Hir Infotech is purpose-built for B2B enterprise and mid-market clients who need more than a one-time data dump — they need a long-term, reliable data partner. Our managed raw data service includes dedicated project managers, custom extraction schemas, quality assurance workflows, and compliance documentation as standard. We serve clients across e-commerce, financial services, healthcare, real estate, logistics, travel, insurance, and SaaS — delivering raw datasets that meet GDPR, CCPA, ISO 27001, and the 2026 EU AI Act requirements. With a proven track record across 40+ countries, 2,745+ satisfied clients, and 13+ years of domain expertise, Hir Infotech is the raw data partner enterprises trust when accuracy, scale, and compliance are non-negotiable.
Industry We Serve
Case Studies
Client Background
A mid-market retail technology company based in Austin, Texas, operating a price comparison platform for consumer electronics across 12 US states, with annual revenue exceeding $45M.
Challenge
The client’s internal team was manually collecting pricing data from over 200 competitor product pages daily — a process consuming 40+ analyst hours per week, generating outdated data by the time it reached the pricing team, and producing a 12–15% error rate that was feeding incorrect recommendations into their dynamic pricing engine.
Solution
Hir Infotech designed and deployed a custom AI-driven raw data extraction pipeline targeting 200+ e-commerce sources including Amazon, Best Buy, Walmart, Newegg, and B&H Photo. The solution included intelligent anti-block rotation, hourly price refresh cycles, and automatic normalization of product attributes across inconsistent source formats. All data was delivered via REST API directly into the client’s pricing platform in real time.
Results
- 94% reduction in manual analyst hours spent on data collection
- Data freshness improved from 24-hour lag to real-time (sub-60-minute updates)
- Pricing accuracy improved by 23%, directly improving margin optimization outcomes
- The client scaled from 200 to 850 product sources without adding headcount
Client Testimonial
“Hir Infotech completely transformed how we access market data. What used to take our team 40 hours a week now happens automatically, accurately, and in real time. Their raw data pipeline is genuinely mission-critical infrastructure for us now.”
— VP of Product, Retail Technology Company, Austin, TX
Client Background
A London-based B2B SaaS company providing revenue intelligence tools for mid-market sales teams in the UK and broader European market. The company had a 35-person sales team operating across the UK, Germany, and France.
Challenge
The client was relying on a static third-party CRM database that had a 34% data decay rate — meaning one in three contact records was outdated, resulting in high email bounce rates (38%), poor outreach conversion, and significant waste in their sales development function. They needed a scalable source of fresh, accurate firmographic and contact-level raw data to rebuild their prospecting infrastructure.
Solution
Hir Infotech implemented a continuous raw data collection program targeting UK Companies House, LinkedIn public profiles, business directories including Yell (UK), PagesJaunes (France), and Wer-zu-wem (Germany), plus industry-specific trade portals. Data was structured to match the client’s CRM schema (HubSpot) and refreshed on a bi-weekly cycle with full deduplication and validation.
Results
- Email bounce rate reduced from 38% to under 6%
- Sales-qualified lead volume increased by 47% within 90 days
- CRM data accuracy reached 96.1% at first refresh
- The sales team expanded outreach from 3 to 7 European markets using the enriched raw dataset
Client Testimonial
“The quality of raw data Hir Infotech delivered made an immediate difference to our outreach performance. Our bounce rate collapsed, and our pipeline quality improved measurably within weeks. They understood our compliance needs from day one.”
— Chief Revenue Officer, B2B SaaS Company, London, UK
Client Background
A PropTech startup headquartered in Melbourne, Australia, building an AI-powered residential property valuation and investment intelligence platform for the Australian and New Zealand markets. The company had recently closed a Series A round and needed to scale its data infrastructure rapidly.
Challenge
The company was manually curating property data from Domain.com.au, realestate.com.au, CoreLogic, and state government property databases. The process was inconsistent, took 3–5 business days per dataset update, and the data quality was insufficient to power their machine learning valuation models — which required at minimum 98% field-level accuracy across 40+ property attributes.
Solution
Hir Infotech built a fully automated raw property data extraction system covering 6 major Australian property platforms, state land title registries, and suburb-level demographic data sources. The pipeline delivered 40+ structured property attributes per listing — including price history, days on market, inspection dates, zoning classifications, and nearby infrastructure data — refreshed every 48 hours via a cloud-delivered API.
Results
- Property data refresh reduced from 5 business days to 48 hours
- Field-level data accuracy reached 99.1%, meeting ML model thresholds
- Valuation model performance improved by 31% post-data upgrade
- The platform expanded from 2 to all 6 Australian states within 6 months
Client Testimonial
“Hir Infotech gave us the data foundation our AI models needed to actually work. The accuracy and consistency of their raw property data feeds is something we simply couldn’t achieve internally. It’s been a genuine product accelerator for us.”
— CTO, PropTech Startup, Melbourne, Australia
Client Background
A quantitative hedge fund based in Frankfurt, Germany, with €2.3B AUM, operating algorithmic trading strategies across European equities, ETFs, and fixed-income instruments. The fund’s quant team required high-frequency alternative data to power sentiment-driven trading signals.
Challenge
The fund’s existing data vendors provided end-of-day summaries at significant cost ($180K/year) but lacked granularity, source diversity, and the real-time frequency needed for intraday signal generation. The quant team needed raw, unprocessed news and social sentiment data from 500+ European financial media sources, refreshed at sub-hourly intervals.
Solution
Hir Infotech designed a specialized financial raw data extraction layer targeting over 500 European financial news outlets, ECB publications, Bundesbank reports, earnings call transcripts, regulatory filings, and German/French/Dutch social finance communities. All raw text data was delivered in structured JSON format with source metadata, publish timestamps, and entity tagging — ready for NLP processing by the fund’s internal ML models.
Results
- Data source coverage expanded from 80 to 500+ financial sources
- Refresh latency reduced to 20-minute intervals from end-of-day delivery
- Annual data acquisition cost reduced by 62% versus previous vendor
- Two new trading strategies were launched using the enriched raw sentiment dataset within 4 months
Client Testimonial
“Hir Infotech delivered the depth and speed of raw financial data that our quant strategies required — at a fraction of what we were paying our previous vendor. Their structured delivery format integrated seamlessly with our NLP pipeline.”
— Head of Quantitative Research, Hedge Fund, Frankfurt, Germany
Client Background
A travel technology company based in Chicago, Illinois, operating a fare intelligence SaaS product used by 300+ travel agencies and corporate travel management companies across the USA, UK, Spain, and Italy.
Challenge
The client needed to track airfare, hotel, and car rental pricing across 50+ booking platforms in real time to power their price prediction and alerting engine. Manual data collection was entirely infeasible at this scale, and off-the-shelf scraping tools kept breaking due to the JavaScript-heavy, dynamically priced nature of travel booking platforms.
Solution
Hir Infotech deployed a resilient raw data extraction infrastructure specifically optimized for travel platforms — including Expedia, Booking.com, Kayak, Google Flights, Ryanair, Vueling, and Trenitalia — using headless browser automation, session management, and adaptive rate control. Data was delivered in structured CSV and API format, covering 180+ origin/destination pairs, with 4-hour refresh cycles and historical pricing archives.
Results
- 98.7% extraction success rate across all 50+ travel platforms
- Pricing data latency reduced to 4-hour refresh cycles from 24-hour
- The client onboarded 80 new agency customers within 6 months citing data quality improvements
- Fare prediction accuracy in their product improved by 18%
Client Testimonial
“We had tried three other scraping vendors before Hir Infotech. None of them could handle the complexity of travel booking platforms at scale. Hir Infotech not only solved the technical problem but delivered enterprise-grade reliability from day one.”
— Head of Data, Travel Technology Company, Chicago, IL
Client Background
A Stockholm-based management consultancy providing procurement advisory services to Nordic and EU government agencies. The firm bid on over 200 public contracts per year across Sweden, Denmark, Iceland, Austria, and the Netherlands.
Challenge
The company’s business development team was manually monitoring TED (EU), Visma, e-Avrop, and individual Swedish municipal tender portals — a process consuming 25 hours per week and frequently missing relevant opportunities due to the fragmentation of procurement data across dozens of national and regional platforms.
Solution
Hir Infotech built a raw tender data aggregation pipeline covering 40+ European public procurement portals — including TED Europe, Mercell, Byggfakta, and national platforms across all Nordic countries plus Germany, Austria, and France. Tenders were extracted, deduplicated, and classified by CPV code, contract value, deadline, and contracting authority — delivered daily into the client’s CRM via webhook integration.
Results
- Tender monitoring time reduced from 25 to 3 hours per week
- Relevant tender identification increased by 83%
- The firm submitted 47 more proposals in the first year post-implementation
- Contract win rate improved by 22% due to earlier bid preparation timelines
Client Testimonial
“What used to require a full-time analyst now runs automatically. Hir Infotech’s raw tender data pipeline covers every relevant procurement portal across the Nordics and Europe. It has directly contributed to revenue growth for our firm.”
— Director of Business Development, Management Consultancy, Stockholm, Sweden
Client Background
A Boston-based HealthTech company building a physician and healthcare provider finder platform for US insurance networks, covering 48 states and 15 specialty categories.
Challenge
The client needed a continuously refreshed database of over 900,000 US healthcare providers — including contact details, specialty, NPI numbers, insurance acceptance, and location data — sourced from CMS databases, state medical boards, hospital websites, and insurance directories. Manual maintenance of this dataset was generating a 28% annual data decay rate, causing broken patient referral workflows.
Solution
Hir Infotech implemented a quarterly-refreshed raw data extraction program targeting CMS Provider of Services files, state medical board registries, Healthgrades, Zocdoc, and insurance network directories across all 48 states. The pipeline structured and validated provider data against NPI registry records, flagging inconsistencies and updates in real time. Data was delivered in SQL-compatible format with full CDC (change data capture) logging.
Results
- Provider data accuracy improved from 72% to 97.4%
- Data decay rate reduced from 28% to under 4% per quarter
- Patient referral workflow errors reduced by 91%
- The platform expanded from 12 to 48 US states using the refreshed dataset
Client Testimonial
“Our platform’s core value depends on having accurate, up-to-date provider data. Hir Infotech built a raw data pipeline that keeps our directory genuinely current — something we simply couldn’t do internally at this scale.”
— Chief Data Officer, HealthTech Company, Boston, MA
Real-World Success: Case Studies
Client Background
A mid-market retail technology company based in Austin, Texas, operating a price comparison platform for consumer electronics across 12 US states, with annual revenue exceeding $45M.
Challenge
The client’s internal team was manually collecting pricing data from over 200 competitor product pages daily — a process consuming 40+ analyst hours per week, generating outdated data by the time it reached the pricing team, and producing a 12–15% error rate that was feeding incorrect recommendations into their dynamic pricing engine.
Solution
Hir Infotech designed and deployed a custom AI-driven raw data extraction pipeline targeting 200+ e-commerce sources including Amazon, Best Buy, Walmart, Newegg, and B&H Photo. The solution included intelligent anti-block rotation, hourly price refresh cycles, and automatic normalization of product attributes across inconsistent source formats. All data was delivered via REST API directly into the client’s pricing platform in real time.
Results
- 94% reduction in manual analyst hours spent on data collection
- Data freshness improved from 24-hour lag to real-time (sub-60-minute updates)
- Pricing accuracy improved by 23%, directly improving margin optimization outcomes
- The client scaled from 200 to 850 product sources without adding headcount
Client Testimonial
“Hir Infotech completely transformed how we access market data. What used to take our team 40 hours a week now happens automatically, accurately, and in real time. Their raw data pipeline is genuinely mission-critical infrastructure for us now.”
— VP of Product, Retail Technology Company, Austin, TX
Client Background
A London-based B2B SaaS company providing revenue intelligence tools for mid-market sales teams in the UK and broader European market. The company had a 35-person sales team operating across the UK, Germany, and France.
Challenge
The client was relying on a static third-party CRM database that had a 34% data decay rate — meaning one in three contact records was outdated, resulting in high email bounce rates (38%), poor outreach conversion, and significant waste in their sales development function. They needed a scalable source of fresh, accurate firmographic and contact-level raw data to rebuild their prospecting infrastructure.
Solution
Hir Infotech implemented a continuous raw data collection program targeting UK Companies House, LinkedIn public profiles, business directories including Yell (UK), PagesJaunes (France), and Wer-zu-wem (Germany), plus industry-specific trade portals. Data was structured to match the client’s CRM schema (HubSpot) and refreshed on a bi-weekly cycle with full deduplication and validation.
Results
- Email bounce rate reduced from 38% to under 6%
- Sales-qualified lead volume increased by 47% within 90 days
- CRM data accuracy reached 96.1% at first refresh
- The sales team expanded outreach from 3 to 7 European markets using the enriched raw dataset
Client Testimonial
“The quality of raw data Hir Infotech delivered made an immediate difference to our outreach performance. Our bounce rate collapsed, and our pipeline quality improved measurably within weeks. They understood our compliance needs from day one.”
— Chief Revenue Officer, B2B SaaS Company, London, UK
Client Background
A PropTech startup headquartered in Melbourne, Australia, building an AI-powered residential property valuation and investment intelligence platform for the Australian and New Zealand markets. The company had recently closed a Series A round and needed to scale its data infrastructure rapidly.
Challenge
The company was manually curating property data from Domain.com.au, realestate.com.au, CoreLogic, and state government property databases. The process was inconsistent, took 3–5 business days per dataset update, and the data quality was insufficient to power their machine learning valuation models — which required at minimum 98% field-level accuracy across 40+ property attributes.
Solution
Hir Infotech built a fully automated raw property data extraction system covering 6 major Australian property platforms, state land title registries, and suburb-level demographic data sources. The pipeline delivered 40+ structured property attributes per listing — including price history, days on market, inspection dates, zoning classifications, and nearby infrastructure data — refreshed every 48 hours via a cloud-delivered API.
Results
- Property data refresh reduced from 5 business days to 48 hours
- Field-level data accuracy reached 99.1%, meeting ML model thresholds
- Valuation model performance improved by 31% post-data upgrade
- The platform expanded from 2 to all 6 Australian states within 6 months
Client Testimonial
“Hir Infotech gave us the data foundation our AI models needed to actually work. The accuracy and consistency of their raw property data feeds is something we simply couldn’t achieve internally. It’s been a genuine product accelerator for us.”
— CTO, PropTech Startup, Melbourne, Australia
Client Background
A quantitative hedge fund based in Frankfurt, Germany, with €2.3B AUM, operating algorithmic trading strategies across European equities, ETFs, and fixed-income instruments. The fund’s quant team required high-frequency alternative data to power sentiment-driven trading signals.
Challenge
The fund’s existing data vendors provided end-of-day summaries at significant cost ($180K/year) but lacked granularity, source diversity, and the real-time frequency needed for intraday signal generation. The quant team needed raw, unprocessed news and social sentiment data from 500+ European financial media sources, refreshed at sub-hourly intervals.
Solution
Hir Infotech designed a specialized financial raw data extraction layer targeting over 500 European financial news outlets, ECB publications, Bundesbank reports, earnings call transcripts, regulatory filings, and German/French/Dutch social finance communities. All raw text data was delivered in structured JSON format with source metadata, publish timestamps, and entity tagging — ready for NLP processing by the fund’s internal ML models.
Results
- Data source coverage expanded from 80 to 500+ financial sources
- Refresh latency reduced to 20-minute intervals from end-of-day delivery
- Annual data acquisition cost reduced by 62% versus previous vendor
- Two new trading strategies were launched using the enriched raw sentiment dataset within 4 months
Client Testimonial
“Hir Infotech delivered the depth and speed of raw financial data that our quant strategies required — at a fraction of what we were paying our previous vendor. Their structured delivery format integrated seamlessly with our NLP pipeline.”
— Head of Quantitative Research, Hedge Fund, Frankfurt, Germany
Client Background
A travel technology company based in Chicago, Illinois, operating a fare intelligence SaaS product used by 300+ travel agencies and corporate travel management companies across the USA, UK, Spain, and Italy.
Challenge
The client needed to track airfare, hotel, and car rental pricing across 50+ booking platforms in real time to power their price prediction and alerting engine. Manual data collection was entirely infeasible at this scale, and off-the-shelf scraping tools kept breaking due to the JavaScript-heavy, dynamically priced nature of travel booking platforms.
Solution
Hir Infotech deployed a resilient raw data extraction infrastructure specifically optimized for travel platforms — including Expedia, Booking.com, Kayak, Google Flights, Ryanair, Vueling, and Trenitalia — using headless browser automation, session management, and adaptive rate control. Data was delivered in structured CSV and API format, covering 180+ origin/destination pairs, with 4-hour refresh cycles and historical pricing archives.
Results
- 98.7% extraction success rate across all 50+ travel platforms
- Pricing data latency reduced to 4-hour refresh cycles from 24-hour
- The client onboarded 80 new agency customers within 6 months citing data quality improvements
- Fare prediction accuracy in their product improved by 18%
Client Testimonial
“We had tried three other scraping vendors before Hir Infotech. None of them could handle the complexity of travel booking platforms at scale. Hir Infotech not only solved the technical problem but delivered enterprise-grade reliability from day one.”
— Head of Data, Travel Technology Company, Chicago, IL
Client Background
A Stockholm-based management consultancy providing procurement advisory services to Nordic and EU government agencies. The firm bid on over 200 public contracts per year across Sweden, Denmark, Iceland, Austria, and the Netherlands.
Challenge
The company’s business development team was manually monitoring TED (EU), Visma, e-Avrop, and individual Swedish municipal tender portals — a process consuming 25 hours per week and frequently missing relevant opportunities due to the fragmentation of procurement data across dozens of national and regional platforms.
Solution
Hir Infotech built a raw tender data aggregation pipeline covering 40+ European public procurement portals — including TED Europe, Mercell, Byggfakta, and national platforms across all Nordic countries plus Germany, Austria, and France. Tenders were extracted, deduplicated, and classified by CPV code, contract value, deadline, and contracting authority — delivered daily into the client’s CRM via webhook integration.
Results
- Tender monitoring time reduced from 25 to 3 hours per week
- Relevant tender identification increased by 83%
- The firm submitted 47 more proposals in the first year post-implementation
- Contract win rate improved by 22% due to earlier bid preparation timelines
Client Testimonial
“What used to require a full-time analyst now runs automatically. Hir Infotech’s raw tender data pipeline covers every relevant procurement portal across the Nordics and Europe. It has directly contributed to revenue growth for our firm.”
— Director of Business Development, Management Consultancy, Stockholm, Sweden
Client Background
A Boston-based HealthTech company building a physician and healthcare provider finder platform for US insurance networks, covering 48 states and 15 specialty categories.
Challenge
The client needed a continuously refreshed database of over 900,000 US healthcare providers — including contact details, specialty, NPI numbers, insurance acceptance, and location data — sourced from CMS databases, state medical boards, hospital websites, and insurance directories. Manual maintenance of this dataset was generating a 28% annual data decay rate, causing broken patient referral workflows.
Solution
Hir Infotech implemented a quarterly-refreshed raw data extraction program targeting CMS Provider of Services files, state medical board registries, Healthgrades, Zocdoc, and insurance network directories across all 48 states. The pipeline structured and validated provider data against NPI registry records, flagging inconsistencies and updates in real time. Data was delivered in SQL-compatible format with full CDC (change data capture) logging.
Results
- Provider data accuracy improved from 72% to 97.4%
- Data decay rate reduced from 28% to under 4% per quarter
- Patient referral workflow errors reduced by 91%
- The platform expanded from 12 to 48 US states using the refreshed dataset
Client Testimonial
“Our platform’s core value depends on having accurate, up-to-date provider data. Hir Infotech built a raw data pipeline that keeps our directory genuinely current — something we simply couldn’t do internally at this scale.”
— Chief Data Officer, HealthTech Company, Boston, MA
Working with Hir Infotech
Data you can trust
Rely on Hir Infotech for 95%+ accurate data, meticulously verified to fuel your B2B success. Our global scraping solutions deliver trusted insights for confident decision-making worldwide.
Decades of experience
With 12+ years of expertise, Hir Infotech has served 2745+ clients globally. Our proven scraping solutions drive B2B success across the USA, Europe, and Australia.
Legal peace of mind
Rely on Hir Infotech for 95%+ accurate data, meticulously verified to fuel your B2B success. Our global scraping solutions deliver trusted insights for confident decision-making worldwide.
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Ready to Power Your Business with Precision Raw Data?
At Hir Infotech, we have spent 13+ years helping 2,745+ clients across the USA, Europe, and Australia turn raw web data into their most powerful competitive asset. Our AI-driven extraction pipelines deliver structured, accurate, compliant raw datasets — tailored to your industry, your sources, and your delivery format.
Whether you need a one-time dataset or a real-time ongoing data feed, our team is ready to build your custom raw data solution in days, not months.
Trusted by enterprises across 40+ countries. 13+ years of raw data expertise. 99.2% data accuracy guaranteed.
Unlock Business Growth with Expert Raw Data Solutions
Benefits of Raw Data Services
Flexible Pricing Models
Project-Based (Flat Fee) Pricing
A one-time fee is charged for a specific project, regardless of volume or duration, based on scope and complexity.
Hourly or Time-Based Pricing
Billed based on the time spent developing, running, or maintaining the scraper, often used for custom or consulting-heavy projects.
Pay-As-You-Go
Charged based on actual usage, such as per request, per GB of bandwidth, or per page scraped, with no fixed commitment.
Subscription-Based Pricing
pay a recurring fee (monthly or annually) for access to scraping services, often tiered based on usage limits like the number of requests, pages scraped, or data points extracted.
Hir Infotech’s Web Scraping Methodology
1
Understanding Your Goals
We begin by collaborating with you to define your data needs—be it for a one-time project, recurring insights, or custom solutions. Whether you opt for Pay-As-You-Go flexibility, a Project-Based Flat Fee, Hourly expertise, or a Subscription plan, we align our approach to your objectives.
2
Target Identification & Planning
Our team identifies the websites and data sources critical to your project. We analyze site structures, assess complexity (e.g., static vs. dynamic content), and plan the most efficient scraping strategy, ensuring compliance with public data access norms.
3
Advanced Data Extraction
Using cutting-edge tools and custom-built scrapers, we extract data at scale. We tackle challenges like JavaScript-rendered pages or anti-scraping measures with techniques such as:
- Rotating proxies to avoid blocks.
- Headless browsers (e.g., Selenium) for dynamic content.
- Optimized request pacing to mimic human behavior.
4
Data Processing & Quality Control
Raw data is parsed, cleaned, and structured into formats like CSV, JSON, or Excel. We remove duplicates, correct errors, and validate accuracy to ensure you receive reliable, ready-to-use datasets.
5
Delivery Tailored to You
Depending on your pricing model, we deliver results how and when you need them:
- Pay-As-You-Go: On-demand data for ad-hoc use.
- Project-Based: Complete datasets for one-off projects.
- Hourly: Iterative updates during custom development.
- Subscription: Regular, automated feeds for ongoing insights.
6
Ongoing Support & Optimization
We monitor site changes, adapt scrapers as needed, and provide support to keep your data flowing seamlessly. Subscription clients enjoy continuous updates, while Hourly clients benefit from hands-on refinements.
Let's build something great together.
Contact us for top-tier talent and exceptional results.
We’ve been working with Hir Infotech for our data scraping needs, and they have exceeded our expectations. The data they provide us is always accurate, timely and helps us make more informed decisions. The team at Hir Infotech is always responsive, and we appreciate their high level of expertise.
The data scraping services provided by Hir Infotech have been instrumental in helping us stay ahead of the competition. We now have access to real-time pricing and product data, allowing us to adjust our strategy and remain competitive.
we are incredibly grateful for the partnership we’ve developed with Hir Infotech. Their data scraping services have helped us improve our marketing strategies and drive growth for our clients. We highly recommend their services to any advertising & marketing company looking to gain a competitive edge.
Frequently Asked Questions
What exactly is raw data, and how is it different from processed or enriched data?
Raw data refers to unprocessed, unstructured information collected directly from its original source — websites, directories, APIs, databases, and digital platforms — before any cleaning, transformation, or analysis has been applied. At Hir Infotech, we collect this raw data and then structure, normalize, and validate it into clean, schema-aligned datasets. This is distinct from pre-enriched commercial data products, which are often generic, stale, and shared with thousands of buyers. Our raw data is custom-collected for your specific use case, ensuring relevance, freshness, and exclusivity.
How do you ensure the raw data you collect is GDPR-compliant for our European operations?
Compliance is embedded into every step of our raw data collection process. We only collect publicly available data from lawful sources, and we operate under a documented compliance framework that addresses GDPR Article 6 lawful bases, data minimization principles, and retention policies. For enterprise clients operating in Germany, France, the Netherlands, Sweden, Austria, and across the EU, we provide full data lineage documentation, processing records, and contractual data processing agreements (DPAs) as standard. We also adhere to the 2026 EU AI Act requirements for clients using raw data in AI training and model development.
What industries do you serve with raw data extraction services?
Hir Infotech delivers raw data services across a broad range of industries, including e-commerce and retail, financial services and fintech, healthcare and life sciences, real estate and PropTech, travel and hospitality, logistics and supply chain, insurance, legal tech, SaaS and technology, government and public sector, and media and publishing. Our extraction frameworks are industry-specific — built around the data structures, source ecosystems, and compliance requirements of each vertical — ensuring maximum relevance and accuracy regardless of your sector.
How fast can Hir Infotech set up a raw data extraction pipeline for our business?
For most standard raw data projects, we can have a fully operational extraction pipeline live within 5–10 business days from project scoping. Complex enterprise engagements involving multiple sources, custom schema mapping, or compliance documentation typically complete onboarding within 15–20 business days. We offer an initial free data sample within 24–48 hours of receiving your requirements, allowing you to validate data quality and format before committing to a full engagement.
What formats do you deliver raw data in, and can it integrate with our existing tools?
We deliver structured raw datasets in all major formats: CSV, JSON, XML, Excel, SQL, and Parquet. We also offer direct API delivery via REST endpoints and webhook integrations for real-time or near-real-time use cases. Our data pipelines are pre-mapped for compatibility with the most widely used enterprise data platforms, including Snowflake, Google BigQuery, AWS S3, Databricks, Salesforce, HubSpot, Power BI, Tableau, and Looker — minimizing integration effort on your engineering team.
How do you handle websites that use anti-scraping protections, JavaScript rendering, or frequent layout changes?
Hir Infotech’s extraction infrastructure is purpose-built for complex, protected web environments. Our AI-driven bots handle JavaScript-rendered pages via headless browser automation (Playwright, Puppeteer), manage CAPTCHAs intelligently, use adaptive proxy rotation across residential and datacenter IP networks, and include automatic schema adaptation when source-side layout changes are detected. Our average extraction success rate across protected enterprise sources is 98.7%, with proactive monitoring ensuring minimal downtime across all active pipelines.
Can you collect raw data continuously, or is it a one-time extraction?
We offer both options. One-time project-based extractions are available for research, market analysis, or database seeding use cases. For clients requiring ongoing data intelligence, we operate fully managed continuous or scheduled raw data pipelines with daily, weekly, bi-weekly, or real-time delivery cycles. All recurring pipelines include proactive source monitoring, automatic error recovery, and SLA-backed uptime commitments — ensuring your data flows without interruption regardless of source-side changes.
How do you guarantee raw data quality, and what is your accuracy benchmark?
Every raw dataset Hir Infotech delivers passes through a five-stage quality assurance workflow: extraction validation, deduplication, field normalization, anomaly detection, and final human QA review for high-sensitivity datasets. Our platform-wide field-level accuracy benchmark is 99.2%, achieved through a combination of AI validation models and human oversight. For enterprise clients, we provide dataset-specific quality reports with field completion rates, confidence scores, and validation logs delivered alongside every dataset.
What is the difference between using Hir Infotech and buying data from a commercial data marketplace?
Commercial data marketplaces sell pre-packaged, generic datasets that are often 6–18 months out of date, shared with thousands of buyers, and not tailored to your specific business requirements. Hir Infotech builds custom raw data pipelines that collect exactly the data you need, from the sources most relevant to your market, refreshed at the frequency your operations demand, and delivered in formats your team can use immediately. This means you get fresh, exclusive, purpose-built data rather than a commodity product — at competitive pricing that typically delivers stronger ROI.
Do you offer a free sample of raw data before we commit to a full project?
Yes. Hir Infotech offers a complimentary raw data sample for all new enterprise and mid-market clients. Simply share your target sources, required fields, and preferred delivery format, and our team will return a validated sample dataset within 24–48 hours — allowing your data and engineering teams to assess quality, structure, and compatibility before making any commercial commitment. There is no obligation attached to the sample request.