How to reduce API integration time: six real results

A fintech CTO told us their API integration took two months. Two months for a payment orchestration API with 12 endpoints. The API wasn't complicated. The documentation was just bad enough that every new integrator hit the same five questions, filed the same support tickets, and waited for the same engineer to answer them.

Ten days after we rebuilt their docs, the same integration took ten days. Same API, same endpoints, same auth flow. The only thing that changed was the documentation surrounding it.

Every extra day of integration time costs you. Engineering hours burned answering questions the docs should answer. Deals stalled in proof of concept while a developer waits for a response on Slack. Customers who quietly switch to a competitor with a better getting-started guide. Slow integration is a revenue leak, and it doesn't show up in any dashboard because the developers who leave never tell you why.

This post shares the before-and-after numbers from six documentation rebuilds we ran for API companies, including PagBank, Tonder, Yuno, and Nayax. Not theory. Not "best practices." The actual levers we pulled and what they moved.

Why API integration takes so long (and why it's rarely the API's fault)

The bottleneck is almost never the API itself, it's the documentation surrounding it. At this point, we're aware developers don't read your docs cover to cover. They scan for three things: a getting-started path, a working code example, and a way to test without breaking anything. If any of those are missing or broken, they stall.

The integration delay usually looks like a developer problem. "They're slow." "They keep asking basic questions." "They should read the docs." But when you watch what actually happens, the developer did read the docs. The quickstart referenced an endpoint that was deprecated two versions ago. The code example used an auth flow that no longer works. The sandbox requires a sales call to access.

This pattern held across every project we worked on. Payments, health tech, developer tools, payment orchestration. Different industries, different API architectures, different team sizes. The same failure mode every time: the API worked fine, the documentation didn't support the developer's actual workflow.

The frustrating part is that the fix is almost always the same set of changes. A working quickstart. Current code examples. Clear auth docs. A sandbox. The companies that do this well measure integration time in minutes. The ones that don't measure it in weeks

The six rebuilds: before and after

Across six documentation projects, we tracked what changed in integration time, support load, and adoption. Here's what the numbers looked like.

None of these companies changed their API. The code was the same before and after. The endpoints, the auth scheme, the response formats, all identical. The only variable was the documentation

PagBank: 20 days to 7 days

PagBank's developers were taking 20 days to complete an integration. The docs existed, but the getting-started flow was buried three clicks deep, code examples referenced previous API versions, and error responses weren't documented.

We restructured the portal around the developer's actual journey: sign up, authenticate, make a first call, handle errors, go to production. Each step had working code examples in multiple languages, tested against the current API version. Integration time dropped to 7 days. CSAT jumped from 29% to 89%. Support ticket volume fell by 50%.

Tonder: 2 months to 10 days

Tonder's integration was taking two months. For a payment orchestration API, that's a business problem, not a technical one. New customers were churning during onboarding because they couldn't get through the integration without constant hand-holding from Tonder's engineering team.

The documentation overhaul on Mintlify focused on three things: a clear onboarding path from zero to first transaction, consistent terminology across all endpoints, and a sandbox that worked without a support ticket. Integration time dropped to 10 days. Product adoption doubled. Support costs dropped 80%.

Yuno: 15-20 minutes to first API call

Yuno had the sharpest time-to-first-call improvement in the set. After migrating their documentation from ReadMe to Mintlify and restructuring the getting-started flow, developers could make their first successful API call in 15-20 minutes. Product adoption increased over 50%, and Yuno won the Best Payment API Award, which directly attracted enterprise customers who cited the documentation quality during evaluation.

What is time to first API call (and why it's the metric that matters)

Time to first API call (TTFC) measures how long it takes a new developer to go from signup to a successful API response. It's the single best predictor of whether a developer will complete an integration or abandon it.

Postman coined the term and wrote the canonical piece on why it matters. NordicAPIs expanded on the concept with a practical breakdown of the levers. Both pieces are worth reading. Both are also theoretical. They explain why TTFC matters and which qualitative levers affect it. Neither includes real before-and-after numbers from actual documentation rebuilds.

What's a good TTFC? It depends on your API's complexity. For a simple REST API with token auth, under 15 minutes. For a complex payment orchestration API with OAuth and webhook configuration, under an hour is strong. Yuno's 15-20 minute TTFC for a payment orchestration API is an aggressive benchmark, and they hit it through documentation changes alone.

The gap between signup and first successful call is where most developer drop-off happens. If you're not tracking TTFC, you're guessing about the most important moment in your developer funnel. Most API platforms (Postman, ReadMe, Mintlify) can surface this data. If yours can't, instrument your API gateway to log the time between API key creation and first successful response

The five levers that actually reduced integration time

Across all six projects, the same five documentation changes showed up as the ones that moved the numbers. Not all six projects needed all five. But every project needed at least three.

A working quickstart that gets to "hello world" in under 10 minutes

This was the single highest-impact change in every project. Not a conceptual overview of your API architecture. Not a page explaining your data model. A step-by-step walkthrough that starts with "create an account" and ends with a successful API response.

The quickstart should be the first thing a developer sees after signing up. If it takes more than 10 minutes to complete, it's too long. If it requires reading a separate auth guide first, the auth is part of the quickstart, not a prerequisite.

Code examples that actually run

Every code example should be copy-paste-and-run. Not "here's a conceptual example you'll need to adapt." Not pseudo-code. A real request with real parameters that returns a real response when a developer pastes it into their terminal.

We found broken code examples in every single project we audited. The most common failure: examples that referenced deprecated auth flows or previous API versions. The docs looked complete.

A sandbox or test environment

Developers need to experiment without consequence. If your test environment requires a sales call to access, your time to first API call includes your sales team's response time. That could add days.

The sandbox should be available immediately after signup. No approval process, no "request access" form, no "contact us for test credentials." Self-serve or it doesn't count.

Clear authentication documentation

Auth is where most developers stall first. API keys, OAuth flows, token refresh, scopes. If a developer can't authenticate in under five minutes, everything downstream stops.

The best auth docs we've seen follow a simple pattern: one page, three sections. "Get your API key" (with a direct link to the dashboard). "Make your first authenticated request" (with a curl example). "Common auth errors and how to fix them." That's it.

Error documentation that explains what to do, not just what went wrong

"401 Unauthorized" is a status code. "Your API key may have expired. Generate a new one at Settings > API Keys" is documentation. The difference between those two responses is the difference between a developer fixing the issue in 30 seconds and filing a support ticket that takes a day to resolve.

Document every error code your API returns. For each one, include what it means, what causes it, and what the developer should do about it. This was the change that most directly reduced support ticket volume across all six projects.

How to measure your own integration time

You can't improve what you don't measure. If your team talks about integration time in vague terms ("it takes a while," "it depends"), you don't have a baseline and you won't know if changes are working.

Three metrics to start tracking:

Time to first API call. The gap between API key creation and first successful response. This is your leading indicator. If it's measured in hours or days, your quickstart is failing.

Time to production. The gap between first API call and go-live. This captures the full integration journey, including edge cases, error handling, and webhook configuration. PagBank's drop from 20 days to 7 measured this metric. Tonder's drop from 2 months to 10 days measured this one too.

Support tickets per integration. How many questions each new integrator generates. If every new developer files 3-5 tickets during integration, those tickets are documentation failures. Track the count, read the tickets, and fix the docs that would have prevented them [Internal Link: API documentation services → /services/api-documentation].

Conclusion

Integration time is a documentation problem, not an API problem. In all six projects, the API stayed the same. The code didn't change. The endpoints, the auth scheme, the response formats, all identical. Only the documentation changed, and the results were consistent:

• PagBank went from 20 days to 7. CSAT jumped from 29% to 89%.

• Tonder went from 2 months to 10 days. Adoption doubled. Support costs dropped 80%.

• Yuno got developers to a first API call in 15-20 minutes. Adoption increased over 50%.

• Nayax unified their portal and doubled their yearly integrations while cutting support costs 80%.

The biggest lever is the quickstart. If a developer can't reach "hello world" in under 10 minutes, everything downstream slows down. The second biggest is working code examples. The third is clear auth docs. These three changes appeared in every project.

Start by measuring your time to first API call. If you don't know the number, you can't fix it. If you do know it and it's measured in days instead of minutes, the fix is probably in your docs, not your code.

We've run this playbook six times. If your integration time is longer than it should be, we can tell you why.