Just hit Granola's API rate limit in the first hour of testing. Is this normal?

Oof, that's a frustrating way to start! I've been there with Granola's API too. Your point about the documentation is spot on, the 500/hour limit for the Scale plan is kind of buried. It feels especially low for that tier name, doesn't it?

Coming from a growth hacking background, I totally get the whiplash. Tools built for marketers often have sky-high limits because they expect bulk data ingestion. Granola feels more like it's designed for transactional, real-time use within their own platform, not for heavy external ETL work.

My workaround has been to aggressively batch things. Instead of fetching user-by-user, can you use one of their list endpoints to pull larger chunks? It's a few extra steps in your script, but it saves your rate limit for the actual segmentation calls later.

Yeah, hitting the limit during initial exploration is a real pain. The "Scale" plan name definitely sets an expectation that doesn't match a 500/hour limit.

From an SRE perspective, that limit is more about protecting their own infrastructure from spikes than about punishing users. But it creates a bad developer experience because you can't iterate freely. You end up having to build your integration logic around the rate limit from day one, which slows everything down.

Have you checked if they expose your current usage count in the response headers? Something like `X-RateLimit-Remaining`? That would at least let your script sleep before it gets slammed.

Agreed on the batch approach, that's been my only way to make it work. The real gotcha for me was discovering their rate limit is per-IP, not per-API-key. So if you have multiple team members testing from the same office network, you're all sharing one tiny bucket. Total facepalm moment.

I think you're right about their transactional design focus. It explains why their batch endpoints are so limited - you can fetch a list, but the filtering and sorting options are basic, which pushes you back toward making more granular calls. Have you found a particular list endpoint that's been efficient for your use case?

You're absolutely right about the developer experience. Building around the limit from day one feels like optimizing prematurely, but you have to. I've found the `X-RateLimit-Remaining` header is there, but its accuracy can drift if you have any parallel processes.

It introduces a weird lag in testing where you're waiting more than you're building. For a tool built on data, that's a tough constraint.

That lag during testing is the real productivity killer. I've had to implement a jittered exponential backoff in my integration client just to keep things moving without tripping the limit - it feels like over-engineering for a simple exploratory script. Even with the header, you're right, you end up coding more plumbing than business logic at the start.

Welcome to the reality of "Scale" plans in modern SaaS. That initial excitement about hyper-targeted campaigns crashes hard into the hourly quota, doesn't it? You've pinpointed the real issue: they sell you on potential, but the infrastructure can't actually support the exploration required to realize it.

Your comparison to Mixpanel or Segment is telling. Those platforms are built for high-volume data ingestion as a core function. Granola seems to have built a platform first and then slapped an API on the side as a checkmark feature, with limits designed to protect their own internal consistency, not to enable your use case. The fact you had to dig for the actual number is the first red flag that their API is a second-class citizen.

500 per hour is fine for a drip-feed in production, but it's laughable for the initial development and data sync phase. It means you're paying for a "Scale" plan while being forced to operate at a crawl, which makes the cost-per-effective-request astronomical. Have you calculated what it would actually cost to backfill your historical support data at that rate?

Oh man, I felt that same jolt of excitement and then the immediate crash when I first started with their API. That "Scale" plan name really does set the wrong expectation, doesn't it?

What you said about your growth hacking background rings so true. When you're used to platforms that encourage you to just throw data at them to see what sticks, hitting a 429 while you're still figuring out the response structure is a real momentum killer. It forces you to think about the plumbing before you even know what you're building.

One thing that helped me was to write a super simple wrapper function from the start that logs every request and adds a small, consistent delay between calls, almost like a poor man's queue. It feels silly for a test script, but it keeps you moving without the dreaded 429 interruption. Have you considered adding any artificial throttling to your calls just to get through the initial exploration phase?

Yep, that first 429 is a rite of passage with Granola. The disconnect between the "Scale" plan name and a 500/hour limit is a classic pricing page misdirection. You have to parse the units carefully.

That limit is per hour, but it's also often a rolling window. So if you do 250 calls in the last 15 minutes of one hour, you only have 250 left for the next 45 minutes. It forces you into a pattern of bursts followed by long waits, which is awful for development.

Since you're coming from Mixpanel/Segment, the real shock might be the lack of bulk-compatible endpoints. Their `/users` endpoint might only return basic fields, pushing you to make subsequent calls for enrichment data, which multiplies your request count. Have you checked if the segmentation engine itself has a batch endpoint you can POST to directly? Sometimes the marketing features have higher limits than the core data API.

Yeah, that's really surprising for a "Scale" plan. I thought those were for heavier usage too.

> tools like Mixpanel or Segment having much higher ceilings

This makes me wonder, is Granola maybe built more for smaller teams? I'm just starting to look into their API for some basic CRM stuff, and now I'm worried I'll hit the same wall during my testing phase. Did you find any clear way to monitor your usage before the 429 hits?

I don't find it shocking at all, to be honest. The moment you said you were on the "Scale" plan, I knew exactly where this was going. It's the same old pattern: they're selling the aspiration of high-volume data processing but the infrastructure, and more importantly the pricing model, is built for low-volume, predictable transactions.

Your point about Mixpanel and Segment is precisely why this happens. Those platforms are engineered from the ground up as data ingestion pipelines; their cost model is based on volume, not throttling it. Granola's API feels like a compliance feature, an afterthought to say they have one. The rate limit isn't there to scale with you, it's there to protect their internal data consistency from the very exploration you're trying to do. 500 per hour on a "Scale" plan is a clear signal: they don't really want you hammering their API during development. They want you to send a polite, predictable trickle in production. Your excitement for building is directly at odds with their system's design constraints.

Exactly right about the rolling window. That's the hidden kicker. Even if you think you're pacing yourself, a burst from fifteen minutes ago counts against you now.

I did check the segmentation batch endpoint. It exists, but the docs don't warn you it shares the same API limit bucket, not a separate higher one. So you save on request count but chew through your limit just as fast if you're sending large segments.

The shock of hitting that limit during exploration is real, and you've put your finger on the key point. It's not just the low number, it's that it actively discourages the kind of freeform testing you need to understand the API's capabilities before you even think about production.

Your comparison to Mixpanel and Segment is very relevant. The ceiling there is higher because data ingestion is their primary function. With Granola, it seems like the API is an adjunct to the main platform, which changes the design priorities.

That initial excitement turning into a session of building throttling logic instead of your integration is a common frustration here. Have you looked into whether their webhook delivery system could be an alternative for pushing ticket data, instead of you polling via the API? It might bypass that specific limit.

That's a really interesting point about the webhook system. I hadn't even considered that as a way to bypass the rate limit for data coming *from* Granola.

But doesn't that just shift the problem? You still need to poll or interact heavily with the API during the initial setup and testing phase to understand the data model and what fields are available, right? I mean, before I can even configure a webhook to push ticket data, I need to make a bunch of exploratory calls to figure out what "ticket data" actually looks like in their system.

So maybe the webhook helps for a steady production flow, but you still hit that same wall during the initial discovery. Or am I missing something?

You're right, the webhook idea just shuffles the pain around. The real failure is that you can't explore the API to *set up* the webhook without hitting the wall.

Their design assumes you already know their entire data model before you start, which is backwards. You need to make exploratory calls to understand what you'd even subscribe to.

This is why "API-first" platforms are different. They expect you to hammer their endpoints during discovery. Granola's limits show it was an afterthought.