Edges vs Piloterr
LinkedIn is not "just another URL" — pick an API that treats it that way.
Who this comparison is for
You're the engineer on call when a selector breaks at 2am. You've scraped LinkedIn through a generic API and you're tired of owning the session rotation, anti-bot fingerprint, and parsing logic yourself.
At a glance
The axes that matter when you’re picking between us.
| Topic | Edges | Piloterr |
|---|---|---|
| Vendor focus | LinkedIn-only. 100% of roadmap and ops attention goes to LinkedIn reliability. | Generalist scraping platform. LinkedIn is one target among many. |
| Operational ownership | We own selectors, sessions, anti-bot posture, and breakage response. | You coordinate parsing logic, session management, and incident response. |
| API surface | Action-oriented: "get profile", "search SN", "send connection" — not "scrape URL". | URL-based scraping API; you build the LinkedIn semantic layer yourself. |
| Sales Nav coverage | First-class Sales Navigator actions: saved searches, lead lists, smart links. | Requires custom scraping logic per SN surface. |
| When LinkedIn changes | You get a changelog entry. Zero action required on your side. | You debug the breakage, update selectors, redeploy. |
Pick the right one
Choose Edges when
LinkedIn is production-critical. You want a vendor whose whole job is keeping LinkedIn actions working — not one that treats it as 1 of 500 target sites.
Consider Piloterr when
You scrape dozens of sites and LinkedIn is a minor piece. You're willing to own selector maintenance, session rotation, and breakage response for the LinkedIn slice in exchange for consolidating vendors.
Migration
Map your current Piloterr calls or automations to Edges actions using the Library and the documentation. Ask support for the OpenAPI spec and it drops straight into Postman, Hoppscotch, or any code generator. Share your integration outline and we can suggest parity endpoints and credit estimates.
FAQ
Why not keep using a generic scraper for LinkedIn?
Generic scrapers flex across many domains but shift all the hard parts of LinkedIn — anti-bot, session rotation, parsing, breakage response — onto your team. Fine for experiments. Expensive in engineering time once LinkedIn is production-critical.
How much engineering time does this save?
Teams that switch typically reclaim 5–15 hours of engineering time per month that was spent debugging selectors, rotating sessions, and updating parsing logic after LinkedIn changes.
What about compliance and account safety?
Edges manages session pools and anti-bot posture so individual LinkedIn accounts aren't exposed to your traffic. With generic scrapers, you own this risk directly.
Can Edges handle scale bursts?
Yes — enterprise tier supports committed-rate plans and burst allowances. If you need 10k+ profile reads per hour, talk to sales.
Can I use both Edges and Piloterr?
Yes — a common pattern is Piloterr (or similar) for non-LinkedIn sites and Edges for LinkedIn where reliability matters most.
Build on Edges
Credits-based pricing, SOC 2 Type II, and a growing catalog of LinkedIn actions — see Pricing and Enterprise for scale.
// other comparisons
Edges is not related to LinkedIn and is not an official LinkedIn product.