Data Engineering Services for B2B Data Intelligence Companies
We Know What Drives You
We help sales intelligence providers scale in backend, data pipelines, and delivery. Whether you meet the surging demand in North America or chase growth in Asia-Pacific, we keep your data flows fast and compliant. Our engineers close the gaps you struggle to hire for: Scala, Spark-Hadoop, and cloud-based big data architecture. With AI-powered pipelines, entity resolution, and modern cloud backends, you grow and innovate; customers get fresher data, sharper insights, and faster integrations.
Explosive Growth
Millions of companies, countless sites, public records, and user-contributed streams now demand always-on crawling, parsing, and enrichment.
Performance Matters
Slow queries and clunky integrations frustrate users. The market standard is now low latency, API-first delivery, and frictionless CRM or warehouse sync.
From Static to Dynamic
Buyers expect continuously updated, dynamic feeds that reflect real changes: funding rounds, job moves, and company growth.
AI as Advantage
Buyers expect continuously updated, dynamic feeds that reflect real changes: funding rounds, job moves, and company growth.
Common Struggles We See Among Sales Intelligence Platforms
Data Acquisition Bottlenecks
Websites change daily, defenses get tougher, and niche industries are notoriously hard to cover. Crawlers break, parsers lag, and your coverage thins. Building and maintaining infrastructure that can continuously capture millions of records across the public web, filings, and user streams is a heavy lift.
Data Quality Issues
Volume without quality is a liability. Duplicates, outdated records, and weak entity resolution erode trust fast. Sales teams lose confidence when contact details bounce or when one company appears under five different names. End users expect 95%+ accuracy, fresh updates, and clean enrichment. Delivering that requires constant verification, normalization, and smarter matching logic.
Scaling Constraints
Your dataset is growing, but can your architecture keep up? Legacy systems choke when millions of new records are ingested or when API traffic spikes. Queries slow, exports fail, and infrastructure costs grow. Re-architecting for scale is complex and resource-hungry. Yet without it, your users feel every bottleneck.
Slow Integrations
Every enterprise client wants data delivered in their own way: Salesforce, HubSpot, Snowflake, APIs, batch feeds. But if each integration is a one-off project, your engineers lose weeks and your clients lose patience. A rigid delivery model can stall deals and frustrate large accounts. Buyers now expect plug-and-play data flows, API-first architecture, and instant connections to their stack.
Compliance Pressure
GDPR in Europe, CCPA in California, and new privacy laws worldwide are rewriting the rules for business data. Your platform must prove every record is sourced and processed lawfully, and every request to opt out or delete is honored fast. That means building privacy-by-design: audit trails, suppression lists, consent tagging, and secure storage.
Talent Gaps
It’s not easy to find engineers who can build and scale data pipelines, tune Spark jobs, or architect microservices that process terabytes daily. Competition with big tech for Scala, Spark-Hadoop, and cloud-native talent is fierce. Hiring takes months; attrition sets projects back. Meanwhile, your roadmap demands more capacity than your team can handle.
Our Capabilities for People Search Companies
Intsurfing designs and implements cloud data ingestion pipelines that aggregate information from the web, PDFs, and other sources. Our crawlers adapt to changing websites, so your coverage stays broad and current. We also set up ETL jobs that pull data from partner APIs, registries, and databases, then merge it all into a single feed.
One of Intsurfing’s core strengths is in data cleaning, matching, and enrichment. We implement AI-driven entity resolution algorithms to reduce duplicates and increase the accuracy of linking people to companies. If you struggle with outdated or inconsistent data, we will set up automated verification processes. When needed, our team adds human-in-the-loop tools. Because we believe that higher data quality directly translates to happier customers and a strong reputation in the market.
We engineer containerized, cloud-native systems with APIs, microservices, and serverless workflows. Our team works with the tools that matter in big data: Scala, C#, and Python for core development, Spark and Hadoop for distributed processing, and AWS for cloud-native deployments. Every piece is built with growth in mind: APIs that can handle millions of calls, microservices that scale independently, and serverless flows that keep costs predictable.
Your customers want data where they already work: CRMs, warehouses, or APIs. We build the delivery layer that makes this possible: clean REST APIs, real-time streams, and ready-made connectors for platforms. Instead of one-off projects for every enterprise client, you get a standardized, repeatable system that reduces engineering overhead and opens new revenue streams. Faster integrations mean happier customers and more deals closed.
When your search slows or databases hit their ceiling, we're here to rebuild the foundation. That can mean moving to a modern cloud warehouse, adding distributed search, or breaking monoliths into microservices. Our goal is simple: keep queries fast, APIs responsive, and systems ready for peak loads. With a backend built to scale, your product feels stronger, more reliable, and far more attractive to enterprise clients.
What We've Already Done for Our Clients
PDF data extraction
Learn how Intsurfing parsed 18M PDFs, identified 1.2M turnover data points, and kept costs as low as 0.7 cents per 1,000 files.
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Data collection tool
Learn how Intsurfing developed a data collection platform that allows developers with basic coding skills to get data from online sources.
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Entity resolution solution
Matched 400M records in 40 minutes using Splink on Spark. Achieved 76% deduplication with 85%+ confidence threshold in a fully automated pipeline.
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ETL for India voter data
Learn how Intsurfing arranged the ETL pipeline for our client to collect data on Indian voters from local portals. Sample data included.
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Address processing system
Discover how the Intsurfing team made an address parsing system 2x faster with Redis, new verification algorithms, caching, and deduplication.
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Data Pipeline and Search Engine Optimization
Cut processing time in half, speed up search 10x. Learn how we optimized ETL pipelines, storage, and indexing for real-time data insights.
Learn more->How You Can Work With Us
Outsourcing Data Collection
We take care of sourcing it for you. Our team collects company and contact information from public records, websites, business registries, financial filings, and structured or unstructured web data. We can parse PDFs, scrape dynamic sites, pull from APIs, or process bulk files. You get a ready-to-use dataset, no infrastructure or extra headcount required.
Managed Team Model
Our managed team model gives you a ready squad of Scala, Python, Spark-Hadoop, and cloud engineers in just 1–4 weeks. We handle recruitment and management while you gain free access to our data processing tools. More capacity means faster delivery. Projects that once took a year can now be shipped in a quarter.
Why Leading B2B Data Platforms Partner With Us
- We work like your in-house team, but without hiring
- Start in weeks, even with rare expertise
- Delivered 220+ big data and backend projects
- Experience with processing PII & financial data
- AWS, GCP, Azure, SOC 2 principles, GDPR, CCPA
- AI-first mindset to power your projects
Make big data work for you
Reach out to us today. We'll review your requirements, provide a tailored solution and quote, and start your project once you agree.
Contact us
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