惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

J
Java Code Geeks
G
Google Developers Blog
Blog — PlanetScale
Blog — PlanetScale
U
Unit 42
A
About on SuperTechFans
Vercel News
Vercel News
B
Blog
Martin Fowler
Martin Fowler
MyScale Blog
MyScale Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
腾讯CDC
D
Docker
V
Visual Studio Blog
博客园 - 叶小钗
The Cloudflare Blog
Jina AI
Jina AI
B
Blog RSS Feed
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
WordPress大学
WordPress大学
T
Tailwind CSS Blog
MongoDB | Blog
MongoDB | Blog
D
DataBreaches.Net
月光博客
月光博客
大猫的无限游戏
大猫的无限游戏

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
I built a search engine for 3 million Polish businesses —...
Paweł Sobkow · 2026-05-27 · via DEV Community

Paweł Sobkowiak

Poland has over 3 million registered businesses spread across two separate public registries — KRS (corporations) and CEIDG (sole proprietorships). Finding reliable data about a Polish company used to mean navigating slow government portals, dealing with inconsistent data formats, and manually cross-referencing multiple sources.
So I built nipgo.pl to fix that.

The problem
If you're a B2B sales person, accountant, or procurement manager in Poland, verifying a contractor means:

Going to the KRS portal — slow, no API-friendly interface
Checking CEIDG separately — different format, different search
Cross-referencing VAT status on the Ministry of Finance whitelist
Manually checking if the company has any public procurement history

This is painful. Especially when you need to do it for 50 companies a week.

What nipgo.pl does
nipgo.pl aggregates all of this into one search:

700k+ KRS entities (corporations, partnerships, foundations)
2.6M+ CEIDG entities (sole proprietorships)
VAT status from the Ministry of Finance
Public procurement history (BZP tenders since 2021)
Public subsidies and grants (SUDOP registry)
Contact data scraped from public sources
AI-generated company summaries

Search by company name, NIP (tax ID), REGON, phone number, email, domain, or owner name. Filter by industry (PKD code), region, legal form, registration date, or capital amount.

The data challenge
The hardest part wasn't building the UI — it was the data.
KRS API returns asterisked names for natural persons (GDPR compliance since 2023). Getting full names requires authenticated scraping of PDF registry documents — each one a different format depending on when the company was registered.
CEIDG has ~2.6M records across ~50,000 paginated API pages. Running that takes weeks and requires careful rate limit management across multiple API tokens.
PKD codes (Polish industry classification) exist in two formats — pre-2015 companies use a nested array format, newer ones use flat objects. Handling both without crashes took more debugging than I'd like to admit.
VAT whitelist has an Imperva WAF that limits requests to ~1,400/day from a single IP. Batch endpoints return zero results in practice. Individual lookups only.

What I'd do differently
Start with the data pipeline, not the UI. I spent too much time on the frontend before the data was clean enough to display. A beautiful UI on top of messy data is useless.
Build keyset pagination from day one. OFFSET-based pagination on 2.6M records causes timeout hell at high offsets. Switching to keyset pagination (cursor-based) was a painful but necessary refactor.
Monitor everything early. Data quality issues in public registries are invisible until a user hits an edge case — a company registered in 1994 with a completely different JSON structure, a CEIDG record with a null NIP, a PKD code from a deprecated classification system.

Current state
The platform is live at nipgo.pl with a freemium model:

Free — basic search and registry data
Basic — contact data, CSV export, monitoring, CRM
Pro — financial reports, risk scoring, full history

Still a lot to build — financial statements, ownership graphs, automated change alerts. But the core data is there and it works.

If you're building something similar for another country's business registry, happy to share what I've learned. Drop a comment or reach out at hello@nipgo.pl.

Built with: Next.js, Supabase (PostgreSQL), Python scrapers, Vercel
Data: KRS API, CEIDG API, MF VAT Whitelist, BZP, SUDOP