Decision-grade data, delivered invisibly. We build resilient market intelligence systems that harvest high-volume data from the web, bypass sophisticated anti-bot defenses, and normalize unstructured noise into clean analytical assets. We turn the internet into your private database.
What You'll Get
Robust extraction engines built on Playwright & Scrapy
Residential Proxy Networks to emulate human traffic patterns
Our consultant manages every step to ensure success:
1
Target Reconnaissance: Analyzing the site's structure and anti-bot defenses.
2
Pipeline Architecture: Designing the crawler, proxy rotation, and storage.
3
Development & Evasion: Building the scripts with fingerprint masking.
4
Quality Assurance: validating data integrity against ground truth.
5
Delivery & scheduling: Setting up the cron jobs and API endpoints.
6
Monitoring: Ongoing health checks to detect site layout changes.
Technologies & Tools
Python Scrapy / Playwright Selenium / Puppeteer Bright Data / Smartproxy ZenRows / ScrapingBee AWS Lambda / Google Cloud Run PostgreSQL / Snowflake Airflow (Orchestration)
Frequently Asked Questions
Is web scraping legal?
We adhere to strict ethical guidelines using public data only. We respect robots.txt where legally required and advise on compliance for your specific jurisdiction. We do not extract PII or credentials.
Can you bypass Cloudflare/Akamai?
Yes. We use enterprise-grade residential proxies and browser fingerprint management tools to emulate valid human users, allowing us to access public data even behind sophisticated WAFs.
What if the website changes its layout?
Websites change. Our 'Strategic' and 'Enterprise' plans include 'Self-Healing' maintenance. We monitor the scrapers daily; if a selector breaks, our team updates the code often within 24 hours to ensure continuity.
Do you sell the data or the software?
We build the software *for you*. You own the code, the IP, and the data pipeline. We can operate it as a managed service, but you remain the asset owner.
How fast can you scrape?
We can scale to millions of requests per day using serverless architecture (AWS Lambda). The only limit is typically the target site's capacity, which we respect to avoid DoS issues.
Client Reviews
★★★★ 4.95
based on 204 reviews
★★★★★ 5
Clean competitor pricing feed
We needed daily competitor pricing and stock status across 12 storefronts, including pages that lazy-load variants and hide shipping fees until checkout. AHK.AI scoped the schema with us, built a Python crawler with rotating proxies and headless browsing, and delivered normalized CSVs plus a Postgres insert option. The monitoring alerts caught a layout change within hours. Data quality has been consistent enough to drive our repricing rules without manual spot checks.
Project: Daily scraping of competitor product listings, variants, shipping fees, and inventory into Postgres/CSV for repricing automation
★★★★★ 5
Reliable login-wall scraping
Our use case involved pulling usage metrics from a partner portal behind SSO and occasional MFA prompts. They implemented a Node.js/Puppeteer workflow with session handling and a fallback CAPTCHA path, then output JSON that mapped cleanly to our internal event schema. The code handoff was tidy, with a walkthrough that made it easy for our engineers to maintain. We’ve had stable runs for weeks, and the monitoring notes are actually actionable.
Project: Puppeteer-based scraper for authenticated partner dashboard metrics, exporting normalized JSON to internal ingestion pipeline
★★★★ 4.5
Solid ETL-ready output
We sourced provider directory data for network adequacy analysis, including multi-page workflows with specialty filters, pagination, and occasional modal pop-ups. AHK.AI delivered structured SQL inserts with consistent field naming and clear provenance notes. They were careful about rate limiting and audit logs, which mattered for our compliance team. Minor hiccup early on with a filter edge case, but it was resolved quickly and documented so our analysts could trust the pipeline.
Project: Scraping provider directory entries (NPI, specialties, locations, accepting status) into SQL tables for analytics
★★★★★ 5
Listings captured accurately
We track rental listings and price drops across a couple of big portals that use infinite scroll and heavy AJAX. Their crawler handled scrolling, deduping, and historical snapshots without missing units. Output came as JSON and a clean CSV for our BI tool, including address parsing and standardized sqft/rent fields. They also set up change detection so we can see deltas day-to-day. It’s been a big upgrade from our brittle scripts.
Project: Automated collection of rental listings, price changes, and unit attributes from AJAX-based portals into JSON/CSV snapshots
★★★★★ 5
Handles tough bot defenses
We needed market data from a site protected by Cloudflare and periodic reCAPTCHA challenges. AHK.AI built a production-grade scraper with proxy rotation, fingerprinting controls, and a stable retry strategy. The feed arrives as normalized JSON with timestamps and source identifiers, which made reconciliation straightforward in our risk models. Documentation included troubleshooting steps and clear boundaries on what could break. Uptime has been excellent, and support was prompt when the target changed a header requirement.
Project: Scraping rate tables and instrument metadata from a Cloudflare-protected site into normalized JSON for risk analytics
★★★★ 4.5
Great for SERP research
We run competitive research for clients and needed consistent pulls of ad copy and landing page URLs across several queries. The flow had nested pop-ups and occasional DataDome blocks, which they navigated better than our in-house attempts. Deliverables were CSVs with clean columns plus a quick schema doc so our strategists could filter fast. Only reason it’s not a perfect score: we asked for one extra enrichment field late and it took an extra sprint to add.
Project: Automated collection of search results/ad snippets and landing URLs with anti-bot handling, exported to CSV for campaign research
★★★★★ 5
BOM parts data unified
We scrape distributor catalogs to monitor lead times and pricing for critical components. The tricky part was inconsistent part-number formatting and multi-page spec tabs. AHK.AI normalized MPNs, packaged quantities, and lifecycle status into a single schema and delivered direct database insertion into our MySQL instance. Their monitoring caught when one distributor moved specs behind an AJAX call, and the fix was deployed quickly. Our procurement team now has a dependable dashboard input.
Project: Scraping electronic component distributor catalogs (price breaks, lead times, specs) into MySQL with normalization and monitoring
★★★★ 4
Good, needs more polish
We commissioned a crawler to gather public tender notices and attachments across multiple regional portals with different workflows. The scraper worked and the XML output matched our downstream parser, but the initial run produced a few duplicate records when tenders were updated mid-day. They corrected it by adding a stable unique key strategy and update logic. Documentation was helpful, though I would have liked a clearer runbook for rotating credentials. Overall strong delivery, just not entirely smooth at first.
Project: Multi-portal tender notice scraping with attachment links, exporting XML and handling updates/deduplication logic
★★★★★ 5
Admissions data without headaches
We pulled scholarship and program details from several university sites that bury requirements behind accordions, tabs, and multi-step forms. AHK.AI built a Python-based scraper that navigated those UI patterns and produced a clean JSON feed with consistent fields (deadline, eligibility, tuition range, contact). The handoff included a code walkthrough so our student success team can run it quarterly. The normalized output saved us hours of manual cleanup and reduced errors in our advising database.
Project: Quarterly scraping of program/scholarship pages with dynamic UI elements, normalized into JSON for an advising database
★★★★ 4.5
Tracking updates at scale
We needed automated extraction of shipment status events from a carrier portal that uses Akamai Bot Manager and session timeouts. Their Node.js solution maintained sessions reliably, handled pagination across long event histories, and pushed structured events into our SQL warehouse. The monitoring alerts were useful when the portal changed its endpoint parameters. Performance was solid, though we had to tune polling intervals to avoid throttling during peak season. Net result: fewer manual checks and faster exception handling.
Project: Authenticated scraping of carrier tracking events with anti-bot bypass, inserting normalized status milestones into SQL warehouse
