diff --git a/reCAPTCHA-Enterprise%3A-Handling-Them-at-Scale.md b/reCAPTCHA-Enterprise%3A-Handling-Them-at-Scale.md
new file mode 100644
index 0000000..d1ce7e5
--- /dev/null
+++ b/reCAPTCHA-Enterprise%3A-Handling-Them-at-Scale.md
@@ -0,0 +1,43 @@
+A short switch-over checklist makes the switch smooth: repoint your endpoint at CapSkip, verify a few live solves, and then cut over production. Because the API mirrors major services, most of the work is essentially done.
+
+QA teams run into CAPTCHAs as well, especially on live environments that mirror production. Instead of disabling these tests, teams are able to let CapSkip clear the challenge so the suite remains intact.
+
+Teams migrating from 2Captcha usually expect a painful migration. In reality, because CapSkip emulates the same API, the change comes down to mostly a matter of the endpoint plus keeping the rest as it was.
+
+Test automation teams run into CAPTCHAs too, particularly when testing staging environments that mirror production. Instead of skipping those tests, they can let CapSkip handle the challenge so coverage stays intact.
+
+The v3 flavor works differently: instead of a visible challenge, it scores interactions behind the scenes. Producing a good token requires a solver that handles how v3 works, and CapSkip is designed to handle it, producing tokens in seconds so your flow continues.
+
+A frequent misstep is simply treating every solver as interchangeable. Match the tool to your challenge mix, the scale, and your budget - CapSkip covers the common types at one price, which fits most everyday workloads.
+
+Residential IP pools and residential ones behave in different ways under anti-bot pressure. Regardless of which blend your setup run, CapSkip handles the CAPTCHA locally and adds no extra a remote dependency to the path.
+
+Python projects get a simple path with CapSkip, since it mirrors the request format of popular solving services. In practice, that means aiming existing code at CapSkip with little effort - nothing to rebuild.
+
+Price tracking across dozens of retailers involves constant hits, and plenty of of those pages protect themselves with CAPTCHAs. Clearing the challenges locally keeps the data fresh without runaway costs.
+
+Solid documentation and tutorials shorten adoption faster. From the setup guide to the API docs and the FAQ, most questions have clear answers before ever ask, so your team spends effort on shipping rather than troubleshooting.
+
+A short switch-over plan keeps the move smooth: repoint the API URL at CapSkip, confirm some live solves, then flip the main jobs. Since the request format matches popular services, the bulk of the work is essentially done.
+
+reCAPTCHA v3 takes a different tack: instead of a clickable challenge, it rates behavior silently. Getting a usable token takes tooling that understands the way v3 behaves, and CapSkip is designed to do exactly that, producing results quickly so your pipeline continues.
+
+GeeTest challenges can be notoriously tricky for bots, which is why having a tool that covers them is a real plus. CapSkip solves GeeTest locally, so workflows that depend on these targets do not break whenever the challenge appears.
+
+A short switch-over checklist makes the move smooth: point the endpoint at CapSkip, verify a few real solves, then flip the main jobs. Since the API mirrors major services, most of the work is already done.
+
+The GeeTest slider puzzles can be notoriously tricky for bots, so having a solver that supports them helps a lot. CapSkip solves GeeTest locally, so scripts that depend on these sites do not break when the challenge appears.
+
+The GeeTest slider challenges can be notoriously awkward for automation, which is why running a tool that supports them helps a lot. CapSkip solves GeeTest locally, so scripts that rely on these sites do not break whenever the puzzle shows up.
+
+Behind the scenes, reCAPTCHA v3 hands out a score from watched behavior instead of a single checkbox. Producing a usable token takes a solver built for that model, which is exactly what CapSkip is built for.
+
+Fundamentally, a CAPTCHA solver reads a challenge and returns the solution a site is looking for, so an automated script can continue. The difference with CapSkip is the work stays on your own Windows machine - no challenge data leaves your hardware, and there are no per-solve fees. That combination of privacy and predictable cost is a real advantage for steady automation.
+
+A Python codebase developers have a clean path with CapSkip, which emulates the request format of popular solving services. In practice, that means pointing existing code at CapSkip with little effort - nothing to rebuild.
+
+The developer API was built to emulate the request format of major CAPTCHA-solving services. In practical terms,  [Capskip.com](https://Shorto.link/lillianbarraga) scripts and tools that already target those services are able to switch to CapSkip with minimal changes and zero coding.
+
+Human-verification challenges are everywhere now, and they can stop nearly any hands-off process in its tracks. The good news is that a dedicated solver clears them automatically, and CapSkip takes care of this locally.
+
+A major advantages of processing on your own hardware is cost. Most services charge per solve, so your costs rise as volume increases. CapSkip uses fixed pricing and uncapped solves, so scaling does not mean watching the meter.
\ No newline at end of file