If you're running direct mail, cold outreach, or any campaign that needs verified contact data, I can help. What I do: - Scrape mortgage, deed, and property records from 30+ county recorder portals across the US - Filter and score leads based on your target criteria (name demographics, mortgage amount ranges, property type, date ranges, etc.) - Enrich every lead with phone numbers, current addresses, and age via TruePeopleSearch or Whitepages - Deliver a clean, ready-to-use CSV — no cleanup required on your end Why it works: County recorder data is public record, updated frequently, and captures life events (new mortgages, property ransfers) that signal buying intent. Pair that with verified contact info and you have a list that actually converts. If you have a specific county, state, or lead criteria in mind, send me a DM. Happy to scope it out for you.

Looking to expand my business to new lawyers and attorneys with cold calling. The scraping solutions I plan to sell would be monthly recurring subscriptions. As the cold caller, you would be responsible for calling and closing the leads and I’d pay you a percentage of each monthly deal you close. This incentives both of us to get as many clients as possible Example of solutions I’ve built can be found on my website: Junelabs.dev

Been working on building a fully automated pipeline that scrapes public mortgage records and enriches them with contact info — and after a lot of trial and error, it's actually working. The hard part wasn't the scraping itself. County recorder sites are public data, but the people-search platforms that let you look up contact info from a name and address are heavily protected. We're talking bot detection, IP fingerprinting, TLS fingerprinting, and session binding — basically every layer of protection stacked on top of each other. Now the pipeline runs end to end: - Pulls mortgage records filtered by amount, date range, and borrower demographics - Scores and ranks leads based on name targeting - Looks up phone, address, and age for each lead automatically - Validates every phone number for line type and activity score so you know which ones are actually worth calling Going from raw county data to a clean, enriched, phone-validated call list with zero manual work. Curious how other people are handling lead enrichment — are you doing it manually, using a service, or have you built something yourself?

Pulled 881 pre-foreclosure leads from 2 portals this morning The script scrapes pre-foreclosure listings from Foreclosure.com and RealtyTrac for any market. I have a client interested in Columbia, SC so I started there. Results: - 643 listings from Foreclosure.com (addresses, AVM estimates, property types, bed/bath counts) - 238 listings from RealtyTrac (addresses, lot sqft, estimated values, ROI indicators, status dates) Everything dumps straight into CSV files — ready to skip trace (with my custom WhitePages and TruePeopleSearch scraper), mail, or load into a CRM. The RealtyTrac data even includes coordinates and estimated values so you can filter by equity before you ever pick up the phone. Not the sexiest win but 800 leads sitting in a spreadsheet by end of day feels good. What portals are you all pulling pre-foreclosure data from? Curious what's working in your markets - PropStream, ATTOM, county records, something else?

Shipped two Ohio municipal court scrapers this week (Akron + Cleveland) Been heads down on the Ohio pipeline and got Akron and Cleveland Municipal Court scrapers running end-to-end. Both portals run on Tyler Tech — reCAPTCHA on every search, session cookies, multi-step redirects, and results buried in embedded JSON inside the HTML. Not the kind of site you can hit with a simple GET request. What ended up working: - Browser impersonation - Handling reCAPTCHA v2 on each search - Proxy rotation Each scraper ran ~1,900 company name searches from a shared term list. Both finished with 0 failed searches: - Cleveland → 304 case records - Akron → 592 case records - Roughly 20–25 minutes per court, fully automated. Output is structured CSV with case numbers, filing dates, defendants, case types, addresses, etc. The nice part is these two share almost the same architecture — same portal vendor, same search flow, same parsing logic. Cleveland was first; Akron was mostly a portal URL swap and a few endpoint tweaks. That pattern is making the rest of the Ohio municipal courts go faster. Curious what everyone else has been building lately — what data pipelines have you set up recently? Always interested in seeing how other people are approaching messy public data sources.