Bespoke extraction for the data nobody packages.
When the data you need sits across awkward sources, nested pages or several languages, off-the-shelf datasets fall short. We scope a custom schema with you and build extraction logic to match it, whether for a single research project or an ongoing programme.
Research and strategy teams often need a dataset that does not exist anywhere in ready-made form. The information is public but spread across directories, regulator sites, marketplaces and brand pages, each structured differently and some in Arabic, Portuguese or Bahasa.
You get one coherent dataset built around your question, with fields defined in a data dictionary and every record traceable to its source URL. One-off projects can later be converted into a scheduled feed without rework.
Everything needed to run it in production.
Scoping workshop
We translate your business question into a field list, entity definitions and acceptance criteria before building anything.
Complex navigation
Multi-step flows such as search forms, filters, location selectors and nested detail pages are handled in the crawler logic.
Multilingual parsing
Arabic, accented Latin and CJK text is captured with correct encoding, and key fields can be transliterated or mapped to English labels.
Entity matching
Records from different sources are linked to a common entity, such as the same product, company or venue, using rules and manual review.
Data dictionary
Each delivery includes field definitions, source lists, coverage notes and known limitations.
Path to automation
If the dataset proves valuable, the same extraction logic moves onto a recurring schedule with monitoring.
What lands in your systems.
| record_id | source | city | clinic_name | specialty | consult_fee | currency | language |
|---|---|---|---|---|---|---|---|
| CL-00412 | Directory A | Abu Dhabi | Family Clinic A | Paediatrics | 300 | AED | ar/en |
| CL-00413 | Directory A | Riyadh | Dermatology Centre B | Dermatology | 350 | SAR | ar |
| CL-00587 | Portal C | Kuala Lumpur | Klinik C | General practice | 60 | MYR | ms/en |
| CL-00644 | Portal D | Bogotá | Centro Médico D | Cardiology | 180,000 | COP | es |
| CL-00702 | Directory E | Manchester | Physiotherapy Clinic E | Physiotherapy | 55 | GBP | en |
Illustrative rows. Your schema, field names and formats are agreed during scoping.
Who uses it, and for what.
Deal teams build a market map of a fragmented sector from public directories and company sites. The dataset supports sizing and target screening early in diligence.
Retailers assemble a view of niche categories, such as specialist nutrition or regional brands, that syndicated data misses. The output feeds range reviews directly.
Market entry teams compile competitor positioning, pricing tiers and channel presence in a new country. The research is repeatable when the team revisits the market.
Analysts receive a clean, entity-resolved dataset for a one-off model or study. Source URLs make it straightforward to audit any surprising result.
- Scope. Tell us the sources, fields and frequency. We confirm feasibility within a day.
- Free sample. A real sample from your own target source, in your format.
- Build. Engineers build extractors tuned to each source. No generic templates.
- Validate. Automated and manual QA on every run before anything ships.
- Deliver and monitor. Scheduled delivery, monitored pipelines, fast fixes when sites change.
Related services
Industries that use it
How do you scope a custom project?
We start with the decision the data should support, then agree entities, fields, sources and acceptance criteria. A free sample of 24–48 hours' work lets you check the shape of the data before committing.
Can you handle Arabic or other non-Latin scripts?
Yes. We capture text in its original script with correct encoding and can add transliterated or translated labels for key fields. Encoding checks are part of standard QA.
What if some sources do not have the field we need?
Coverage varies by source, so we report fill rates per field and per source. Where a field is missing we flag it rather than infer a value, and suggest alternative sources where they exist.
Is a one-off extraction cheaper than an ongoing feed?
The initial build effort is similar, but a one-off project has no ongoing monitoring or maintenance costs. Many clients begin with a one-off and move to a schedule once the value is proven.