01
Ticket marketplaces
Compare listing prices and availability without losing event and seating context.
Custom data collection & engineering
ScrapingBuddy.
Website & mobile-app
scraping. Built for you.
Custom scraping, structured datasets and maintained pipelines. Tell us what you need; our team builds and runs the collection.
Website scraping
Public pages, dynamic catalogues and source-specific collection workflows.
Explore collection experienceMobile-app scraping
App-only menus, prices and records, with the location and session context they need.
See our app-data workSelected client work
Built for real operations.
~20MListing records delivered daily2+ years in production
Ticket intelligence
A maintained feed for ticket intelligence.
A daily collection pipeline with event, seating and price context kept together.
42Brands covered in one programme
Restaurant intelligence
Local menu data, connected across brands.
A DoorDash programme bringing locations, menus and prices into one analytical workflow.
4-5 hrsProcessing, down from 3+ days
Data engineering
A shorter path from collected data to delivery.
A redesigned processing stage removed a multi-day bottleneck from a weekly restaurant-data workflow.
Results from individual projects, not service-wide performance guarantees.
Custom scraping / managed data
Your data.
Delivered and maintained.
Structured records that fit your workflow.
Keep source details, identifiers and collection context connected. We build the collection and delivery pipeline around your schema, then maintain the agreed recurring workflow.
Discuss your data needs- 01
Share the requirement.
Send source URLs or app names, the fields you need and your refresh schedule. We assess the collection together.
- 02
Agree a sample.
Confirm sample scope, timing and fees first. We then prepare records for you to review before scaling.
- 03
Build for delivery.
Agree validation, format and destination, with monitoring and maintenance for your recurring collection.
We confirm feasibility, authorized access, availability and project terms together before work starts.
How we workCollection experience
The context behind
useful data.
Explore the records we collect and the comparisons they can support, from local menu prices to changing marketplace inventory.
Explore all use casesCollection examples, not customer or partner endorsements.
02
Restaurants & delivery
Compare local menus and prices across delivery platforms and mobile apps.
03
Retail & marketplaces
Track assortment, stock and offer changes at the product-variant level.
04
Property
Compare asking prices with the location and property details that explain them.
05
Travel & hospitality
Compare hotel and flight offers with their dates, availability and search context.
06
Recruitment
Follow hiring demand by role, employer and location, with the original job detail.
Have a different source in mind? Tell us about your project
Engineering in practice
A closer look at our tools.
Examples of the systems our team builds. Your managed project is designed around your requirements, not a product checklist.
Before we build
From a requirement
to a working feed.
A few things worth knowing before we scope your project.
Book a project callWhat should we send to start a project?
Share representative URLs or app names, the fields you need and how you plan to use the data. Add your markets, refresh schedule and preferred delivery format where known. We review the source and discuss the scope with you; you do not need a finished technical specification to start the conversation.
How are pricing, timing and sample work agreed?
The sources, access requirements, fields, volume, refresh frequency and delivery work shape the estimate. We agree the scope, timing and any sample-work fees with you before that work starts. Use cases show collection experience, not off-the-shelf datasets; availability is confirmed for your project.
Can the output match an existing schema or data warehouse?
Yes, the output is designed around the agreed data contract: field names, types, identifiers, missing-value handling and format. We review sample records against it before scaling. Your delivery destination and integration requirements are part of that discussion.
What happens if a source changes or a collection run is incomplete?
We investigate the affected source and check the output before treating a run as complete. Your project scope defines monitoring, retry handling, maintenance responsibilities and how issues are communicated. If a source change affects coverage or delivery, we review the next steps with you.
Real people behind the pipeline
What are you
working on?
Start with a source, a question, or a sample of the data you need. We will work out the next step together.
A 22-person team in Bangladesh.
Engineering and operations, working together on your data.