Dedicated web data acquisition teams for data-driven companies
Named DataDwip engineers collect, maintain and deliver the web data your product depends on, every day, under a written freshness and data-quality SLA. You add sources. We keep them running.
- Daily OTA rate pipelines
- Continuous manufacturer price feeds
- 1,000+ websites
- 20+ countries
- 50 million records delivered
Your scrapers aren't the product. Fixing them is eating the team that builds it.
If web data feeds your product, three things are true right now:
Sources break every week.
Layout changes, new anti-bot rules and redesigns silently cut records, delay runs or drift your schema. Nobody notices until a customer does.
The next hire won't fix it.
A senior scraping engineer is a six-figure salary plus proxies, browsers, monitoring and someone to cover them when they're out, and their first six months go to the backlog, not the roadmap.
Coverage slips.
The new marketplace, country or portal your customers keep asking for stays on the list because the team is maintaining what already exists.
A dedicated data acquisition team takes the maintenance tail off your engineers and turns coverage into a monthly routine.
What you get
One monthly fee. Everything below is included.
Team
3 named scraping engineers dedicated to your sources, a shared QA/data-quality lead and a delivery manager as your single point of escalation
Source scope
Up to 15 complex sources (marketplaces, OTAs, listing portals, JS-heavy or protected sites) or up to 40 standard sources, mixed by agreed complexity points
Refresh cadence
Daily by default; hourly or multi-daily on agreed sources; real-time by quote
Maintenance
Unlimited breakage fixes on in-scope sources, proactive change detection, regression tests on every fix
New sources
Up to 3 new sources onboarded per month, including schema design, compliance review and QA sign-off
Infrastructure
Proxy pools, headless browsers, scheduling, storage, monitoring and alerting, owned and paid for by DataDwip
Data quality
Automated completeness, type, range, duplicate and drift checks plus manual sample QA before every delivery
Delivery
Amazon S3, Google Cloud Storage, Azure, Snowflake, BigQuery, Redshift, PostgreSQL, or a DataDwip REST API. JSON, CSV or Parquet, in your schema
Reporting
Weekly source-health digest, monthly coverage and quality report, quarterly roadmap review
Communication
Shared Slack channel, two-business-hour response, named escalation contact
Compliance
Per-source terms and robots review, no-PII default, exclusion list honoured within 24 hours, written GDPR/CCPA pack
The SLAs we sign
These go into the contract, with service credits if we miss them.
Freshness
95% of scheduled deliveries inside the agreed window
Delivery timestamp against schedule, reported weekly
Coverage
At least 97% of expected records per source per run
Records delivered against agreed baseline
Data quality
99% of records pass validation; duplicates under 0.5%
Validation report on every delivery
Repair time
Breakage detected within 4 hours, fixed within 24 business hours
Incident log
Schema stability
30 days' notice on any breaking change; additive changes documented weekly
Change log
Response
Two business hours, with IST overlap for US and UK mornings
Ticket timestamps
SLAs start after the onboarding month. Credits are capped at 25% of the monthly fee, and they are paid, not negotiated.
Six quality layers on every delivery
Every run passes automated and manual checks before it reaches your warehouse, so the data you ship to customers is complete, consistent and on schema.
Schema layer
- Matches your agreed schema
- Types and formats validated
Completeness layer
- Coverage as per SLA
- Missing fields flagged
Accuracy layer
- Range and value checks
- 99% of records pass validation
Duplicate layer
- Duplicates under 0.5%
- De-duplicated across runs
Drift layer
- Volume and schema drift detected
- Breakage flagged within 4 hours
Manual QA layer
- Sample review before delivery
- Signed off by your QA lead
Start with a 4-week pilot
See the numbers before you commit to anything.
- Week 1
Audit and first data.
We review two or three of your hardest or most valuable sources, agree the schema and delivery window, complete the compliance review, and deliver first data by day five.
- Weeks 2–4
Daily deliveries, tracked against the SLA.
Every delivery is scored on freshness, coverage and quality. If a source breaks during the pilot, you watch us fix it.
- End of week 4
Scorecard and scope.
You receive the pilot scorecard and a proposed team scope with a source map. If the SLA targets are met in three of the four weeks, we convert to the dedicated team on the terms agreed up front, and the pilot fee is credited against your first month.
If you don't continue, you keep the code and the data.
Built for companies where web data is the product
If your team is hiring scraping or data acquisition engineers, expanding coverage, or firefighting silent breakage, this is the model built for you.
Pricing and retail intelligence platforms.
Thousands of retailer and marketplace pages kept fresh for price monitoring, assortment tracking and digital shelf analytics, extended to new markets without new hires.
Hospitality and travel data providers.
OTA, brand-site and metasearch rates collected daily for rate shopping, parity monitoring and revenue management, on the same schedule your customers price against.
Short-term rental, real estate and automotive data.
Listing inventories, calendars, rents and dealer stock refreshed across portals and countries, with history preserved.
Job and company data providers.
The long tail of career pages, job boards and company websites behind workforce intelligence, sales intelligence and research datasets, maintained as it changes.
Alternative data and research firms.
Web-derived datasets for investors and analysts, with a compliance pack your legal team can review before the first delivery.
AI products and agents.
Clean, structured, continuously updated web data pipelines feeding models, RAG systems and agents, without drift when the sources change.
How your team runs, day to day
Onboard.
Source audit, schema agreement, compliance review, infrastructure provisioned. First sources live within five business days; full team live within two weeks.
Run.
Scheduled collection, monitoring, repairs, validation and delivery every day. Alerts go to your Slack channel the moment a source degrades, with the fix status.
Report.
A weekly source-health digest showing each source's freshness, coverage and quality, and a monthly report you can forward to your own customers.
Expand.
New sources every month, quarterly roadmap reviews, and additional engineers as your data needs grow.
Compliance, built in
Every source is reviewed for terms of service and robots rules before collection starts. We collect public data only. Personal data is excluded by default and collected only where you document a lawful basis. Sources on your exclusion list are dropped within 24 hours. Your legal team receives a written compliance pack covering GDPR and CCPA posture, data handling and retention, and it is updated as your source list changes.
Proof
Daily hotel rate intelligence.
How DataDwip provides a travel company with daily competitor rate data across OTAs to optimise pricing strategies.
Read the case studyContinuous pricing for a leading tire manufacturer.
How ongoing competitor price collection and analysis helped a manufacturer refine its pricing models and market positioning.
Read the case studyWhat a weekly source-health digest looks like.
Per-source freshness, coverage and quality for the week, open incidents with repair status, sources onboarded, and next week's changes.
Request a sample digest
How a dedicated team compares
| In-house hire | Scraping API tools | Project-based scraping vendor | DataDwip dedicated team | |
|---|---|---|---|---|
| Who maintains the scrapers | Your engineer | Your engineer | Nobody after handover | Named DataDwip engineers |
| Infrastructure and proxies | You buy and run | You integrate and pay per request | Vendor, during the project | Included |
| Freshness and quality SLA | None | None | Rare | Written, with credits |
| New sources | When the engineer has time | You build them | New quote each time | Monthly, included |
| Cover for absence | None | N/A | N/A | Built in |
| Monthly cost | Salary plus infrastructure | Usage fees plus engineer time | Unpredictable | One fixed fee |
Pricing, plainly
A dedicated team is a fixed monthly fee that covers engineers, infrastructure, maintenance, quality checks, compliance and delivery. Teams start at a three-month minimum, with discounts for six- and twelve-month terms, and scale in two-engineer increments as your source list grows. The 4-week pilot is fixed-price and credited against your first month. If you ever leave, the code, configurations and data are handed over in full.
Get a scoped quote
Get the Offer & SLA sheet
Everything in one monthly fee, the SLAs we sign, both pilot options and pricing, on six pages you can share with your team.
Frequently asked questions
What clients say about working with us
5.0 average across 38 verified reviews on Clutch and GoodFirms.
- GoodFirms
“With DATADWIP assistance, they managed to detect many defects which would have adverse effects on the customers before the software release.”
In this case, they used curricular knowledge and technical know-how in order to offer the necessary support for learners.
Bertrand PiquardChief Executive Officer, LS GROUP (ex Light And Shadows) - GoodFirms
“Datadwip developed a web scraper based on AI through exhaustive evaluation of our data requirements.”
Data quality management and algorithm creation for web scraping and source identification composed the majority of a Datadwip professional's tasks. Organized datasets contained important price pattern information as well as competitor analysis combined with online user feedback obtained from numerous web-based sources.
James McWalterCEO, https://paces.com - Clutch
“Their technical team was excellent; they were very agile.”
The client has already processed payments in the last few months, and the end customers have used the software as their own. Data Dwip has met the client's expectations by delivering on time and collaborating through Jira, Zoom, and email. Their agile approach and technical expertise are exemplary.
Alexandre RambaudCEO, Agendize
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Put a dedicated team on your web data acquisition
Tell us which sources matter most and when you need the data. You'll have a pilot plan within two business days and first data within five.