We extract prescription drug catalogues, OTC inventory, retail pricing, insurance copay estimates, and delivery coverage zones from Capsule. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Prescription Drugs objects from capsule.com. All fields typed and schema-versioned.
"ndc_code": "00069-3150-83", "generic_name": "Atorvastatin Calcium", "brand_name": "Lipitor", "dosage_form": "Tablet", "strength": "40mg", "retail_price": 145.5, "rx_required": true
| # | ndc_code | generic_name | brand_name | active_ingredients | dosage_form | strength |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for OTC Products objects from capsule.com. All fields typed and schema-versioned.
"sku": "OTC-88492", "product_name": "Zyrtec Allergy Relief", "category": "Allergy & Asthma", "brand": "Zyrtec", "price": 22.99, "stock_status": "In Stock", "size": "30 Tablets"
| # | sku | product_name | category | brand | price | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Insurance objects from capsule.com. All fields typed and schema-versioned.
"drug_id": "DRG-4921", "cash_price": 145.5, "average_copay": 15.0, "tier_status": "Tier 2", "prior_auth_required": false, "step_therapy_flag": false, "quantity_limits": "30 per 30 days"
| # | drug_id | cash_price | average_copay | insurance_networks_accepted | tier_status | prior_auth_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Delivery Coverage objects from capsule.com. All fields typed and schema-versioned.
"zip_code": "10001", "city": "New York", "state": "NY", "delivery_window_available": "Same Day", "pharmacy_hub_location": "Manhattan Hub", "service_status": "Active", "cutoff_time": "14:00"
| # | zip_code | city | state | delivery_window_available | courier_type | pharmacy_hub_location |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Drug Information objects from capsule.com. All fields typed and schema-versioned.
"drug_id": "DRG-4921", "administration_route": "Oral", "storage_instructions": "Store at room temperature", "common_side_effects": "['Nausea', 'Headache', 'Fatigue']", "severe_side_effects": "['Muscle pain', 'Liver problems']", "warnings": "Do not take if pregnant"
| # | drug_id | warnings | contraindications | common_side_effects | severe_side_effects | storage_instructions |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Capsule scraper navigates location-based routing, dynamic React interfaces, and complex drug taxonomies to deliver structured catalogue and pricing data.
Extract generic names, brand names, active ingredients, dosage forms, strengths, and NDC codes across the entire formulary.
Capture cash prices and estimated copays for specific dosage and quantity combinations, timestamped per crawl.
Monitor over-the-counter product availability, pricing, and category placement across different delivery zones.
Extract accepted insurance networks and standard tier statuses for prescription medications.
Map active service zones by iterating through ZIP codes to determine delivery availability and hub assignments.
Extract all available strength and quantity permutations for a given medication to build a complete pricing matrix.
Identify drug manufacturers and distributors listed for specific generic and brand-name medications.
Scrape warnings, contraindications, side effects, and storage instructions surfaced on the medication detail pages.
Run continuous pipelines at daily or weekly cadences to track formulary changes and price fluctuations.
Brief in. Clean data out.
Provide drug names, NDC codes, or ZIP codes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, location spoofing, and session management for capsule.com.
Schema validation, null-rate checks, price-outlier detection, and sample payloads before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern digital pharmacies use complex location routing and single-page application architectures. Here is how we build resilient pipelines.
Capsule's inventory and delivery options vary strictly by geographic location. We inject specific coordinates and ZIP codes into the browser session to map coverage and pricing across multiple metropolitan areas accurately.
Capsule relies heavily on React and dynamic API calls to render drug information and pricing. We run full Playwright browser sessions to hydrate the application state and capture data that headless HTTP clients miss entirely.
Healthcare platform interfaces evolve frequently. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and intercepted XHR responses — so a layout change does not break your data pipeline.
For large drug catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load. You get a clean changelog rather than full re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops — and respond before you notice. SLA uptime is contractual.
Retail pharmacies and telehealth providers monitor cash prices and copay estimates to maintain competitive pricing.
Healthcare analysts track formulary additions, generic substitutions, and OTC category expansion trends.
Digital health platforms map local pharmacy delivery coverage zones to route prescriptions efficiently.
Payers and PBMs analyze accepted networks and tier placements across digital pharmacy platforms.
Manufacturers track stock availability and geographic distribution of their medications.
ML teams use structured medication catalogues and clinical information to train healthcare NLP models.
"Capsule maps the modern pharmacy experience, but extracting their pricing and coverage data requires navigating complex location-based routing and dynamic React interfaces."
Most teams underestimate the investment required: reliable Capsule scraping requires residential proxies, location spoofing, full JavaScript rendering, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our capsule.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, location spoofing, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About capsule.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Capsule is generally permissible under applicable law. DataFlirt targets only public, non-authenticated drug catalogues, pricing, and coverage data. We do not extract personal patient data, circumvent authentication walls, or violate HIPAA regulations.
We utilize Playwright to inject specific geolocation coordinates and ZIP codes into the browser session, allowing us to map coverage areas and extract localized pricing accurately across different metropolitan regions.
Yes. Our pipeline iterates through all available strength and quantity selectors on a medication page to build a complete pricing matrix for every possible permutation.
Full catalogue refreshes at daily or weekly cadences complete within a defined window. Specific pricing monitors can be configured to run more frequently based on your requirements.
Yes. We extract the entire over-the-counter catalogue, including pricing, stock status, descriptions, and category hierarchies.
Absolutely. We provide a sample run of up to 100 medications or specific ZIP codes as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off formulary dump or a continuous price-monitoring feed across multiple ZIP codes — we scope, build, and operate the pipeline. Tell us what you need.
