We collect publicly available data, review every source's terms and robots rules before starting, exclude personal data by default and provide a compliance pack for your legal team. Sources we consider legally contested are flagged in the audit and priced separately or declined.

Managed data acquisition

Dedicated web data acquisition teams for data-driven companies

Q: How is this different from a web scraping service?

A scraping service delivers a dataset. A dedicated team delivers an operation: daily collection, maintenance, infrastructure, quality checks, compliance and delivery under SLA, run by engineers who work only on your sources.

Q: We already have scraping engineers. Why would we add a team?

Keep them. Most clients use the dedicated team to absorb the maintenance tail so their own engineers add sources and build product. Overflow and long-tail sources are the most common starting scope.

Q: Can you handle sites with anti-bot protection or heavy JavaScript?

Yes. Rotating proxies, headless browsers and engineers who specialise in protected and frequently changing sources are part of the standard team.

Q: What happens if you miss an SLA?

You receive a service credit on the next invoice, automatically. Repeated misses trigger a scope review at no cost.

Q: What if a source we need isn't in scope?

New sources are onboarded every month as part of the fee. Larger expansions add engineers in two-person increments.

Q: How quickly can we start?

First pilot data within five business days. A full team is live within two weeks of contract.

Q: Who owns the scrapers and the data?

You do, at every stage, including after exit.

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.

Start a 4-week pilot See what's included

Week 38 · source-health digestlive

Source	Fresh	Cov.	QA	Status
booking.com	100%	99.2%	99.8%	Healthy
expedia.com	100%	98.7%	99.6%	Healthy
agoda.com	86%	97.4%	99.1%	Repaired
brand site (EU)	100%	99.9%	99.9%	Healthy
trivago.de	100%	97.0%	99.3%	Onboarded

1 incident · repaired in 5h 40m · 1 source onboarded

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:

A dedicated data acquisition team takes the maintenance tail off your engineers and turns coverage into a monthly routine.

01
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.
02
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.
03
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.

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.

SLA	Our commitment	How it's measured
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.

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.

Start a 4-week pilot

Built for companies where web data is the product

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.

If your team is hiring scraping or data acquisition engineers, expanding coverage, or firefighting silent breakage, this is the model built for you.

How your team runs, day to day

01
Onboard.
Source audit, schema agreement, compliance review, infrastructure provisioned. First sources live within five business days; full team live within two weeks.
02
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.
03
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.
04
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 study
Continuous 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 study
What 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

Frequently asked questions

How is this different from a web scraping service?

We already have scraping engineers. Why would we add a team?

Can you handle sites with anti-bot protection or heavy JavaScript?

Is this legal?

What happens if you miss an SLA?

What if a source we need isn't in scope?

How quickly can we start?

Who owns the scrapers and the data?

What clients say about working with us

5.0 average across 38 verified reviews on Clutch and GoodFirms.

5.0

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.

Start a 4-week pilot Book a meeting

Managed data acquisition

Web data

Mobile app

API plug & play

Dedicated web data acquisition teams for data-driven companies

Your scrapers aren't the product. Fixing them is eating the team that builds it.

Sources break every week.

The next hire won't fix it.

Coverage slips.

What you get

The SLAs we sign

Start with a 4-week pilot

Audit and first data.

Daily deliveries, tracked against the SLA.

Scorecard and scope.

Built for companies where web data is the product

Pricing and retail intelligence platforms.

Hospitality and travel data providers.

Short-term rental, real estate and automotive data.

Job and company data providers.

Alternative data and research firms.

AI products and agents.

How your team runs, day to day

Onboard.

Run.

Report.

Expand.