Guides · Updated October 2026

Build vs. Buy: Should You Scrape In-House or Hire a Firm?

AI coding assistants changed the build-vs-buy math for web scraping — but not in the direction most people assume. Building got dramatically cheaper. Operating didn't. Here's an honest decision guide from a firm that obviously sells one side of it.

What AI changed

A competent engineer with a coding agent can produce a working scraper for a cooperative site in an afternoon — work that took days in 2020. For one-time collection from lightly-protected sources, the build case has never been stronger, and we'll tell you so if you ask. Point-and-click scraping tools, meanwhile, are increasingly obsolete: AI-assisted code is now faster than configuring them and has no flexibility ceiling.

What AI didn't change

• Anti-bot escalation. Frontier AI models are also increasingly restricted around anything resembling bot-evasion, so the hardest 20% of scraping — the protected sites — is exactly where AI assistance helps least. That share of the web grows every year.
• Operations. Sources change without notice. Someone must monitor every run, notice silent degradation, and fix collectors on someone else's schedule. An AI agent doesn't carry a pager.
• Judgment. Which approach per site, which proxies, how to validate, how to keep costs sane at scale — the same dataset can cost 100x more collected naively than engineered well.
• Accountability. When a feed your business depends on stops, "the AI wrote it" is not a plan.

The real cost lines

Build: engineering time (initial + ongoing maintenance, which for recurring feeds typically exceeds the build within a year), proxy and infrastructure spend, and opportunity cost — what that engineer isn't building instead.
Buy: the vendor's fee, period — if it's fixed. Metered or hourly pricing moves maintenance risk back to you; read the pricing model before the feature list.

A decision rule that holds up

• Build when: one-time or experimental, sources are unprotected, volume is modest, and you have engineering slack.
• Buy when: the data feeds a business process, sources are protected or numerous, you need a defensible provenance story, or your engineers' time is worth more on your actual product.
• Hybrid is often right: build the easy sources in-house, hand the protected or critical ones to a firm. No good vendor objects to this; we work this way with several clients.

Questions that cut through vendor pitches (including ours)

1. What happens, specifically, when a source site changes?
2. Is pricing fixed, or does maintenance cost extra?
3. Can I see validation output, not just the data?
4. What do you decline to collect, and why?
5. What's the exit: do I get my data history if I leave?

A vendor who answers all five crisply is probably safe to hire. Marquee Data's answers: we fix it (included), fixed fees never hourly, yes, anything non-public, and your data is yours.

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