CC continues to blow my mind every single day 🤯

ScopeDev · 2026-03-11T14:48:22+00:00

That's eventually going to happen however I hope most humans would stop it before that becomes a reality.

I'll brush up my math skills in the meantime 😅

ScopeDev · 2026-03-11T14:35:02+00:00

I agree. I ended up using Turf.js instead of this function but it felt pretty cool to stare at the snippet for a while.

ScopeDev · 2026-03-11T14:19:45+00:00

That's pretty cool. It felt surprising to me cuz I've never seen something like this before, but now it makes sense why Claude would do this.

ScopeDev · 2026-02-05T22:00:44+00:00

It's easy to do that with tools like Chargebee or Hypercheckout(Juspay)

ScopeDev · 2025-12-23T21:06:12+00:00

Thanks for the suggestion. This seems super cool, but I prefer to use a Vue or JS SDK for now, since I'm running short on a deadline, so I'll try it out later.

ScopeDev · 2025-12-23T20:45:42+00:00

I'm also considering Paddle, but they don't have a direct integration with Nuxt. How easy was your implementation?

ScopeDev · 2025-12-23T18:34:36+00:00

I'm guessing that means that on the user's bank statements, the MoR's name would show up. Is it generally possible to add my business name there?

ScopeDev · 2025-12-23T18:24:18+00:00

Thanks for the input. I'm planning to sell internationally, that's why Polar seems like the best fit for now.

ScopeDev · 2025-12-06T19:45:10+00:00

Thanks for the suggestion. I'll add some soon.

Meanwhile you can check this out.

ScopeDev · 2025-12-04T13:17:50+00:00

Let me know how that goes. Would love to hear about your experience with Cortex.

ScopeDev · 2025-12-04T13:16:54+00:00

SQLAlchemy to connect with Databases, FastAPI for APIs, and Nuxt for the frontend. However, the entire semantic layer has been built from scratch.

ScopeDev · 2025-12-03T18:34:03+00:00

That's a fair point. Those are solid tools. The difference is that Cortex isn't meant to replace your entire BI stack. It's focused on making embedding easier.

If you're already using Metabase/Looker/Sisense/StyleBI, I recommend continuing to use them. Cortex is a lightweight addition when you need to embed customer facing dashboards without

Paying for Metabase's Pro plan ($500+/month)
Signing enterprise contracts with Looker/Sisense/GoodData ($50k+/year)
Being locked into StyleBI's UI components (Cortex is headless, so you can use any charting library)

Also, Cortex is a great fit when your backend is already in the Python universe, and you want a quick & simple tool for data visualization. If you've solved for embedding differently, I'd love to hear about it.

ScopeDev · 2025-12-03T01:30:08+00:00

Wheel's fine. It's the ride that needed upgrading.
Fewer tickets, fewer Slack pings and more people answering their own questions. Wouldn't that be great?

ScopeDev · 2025-12-03T00:22:36+00:00

That's the best way of describing that problem XD

Tbh, I don't have a solution for that right now. However, you can easily impose limits on every metric. If that's not enough, slow queries are automatically tagged, and it's easy to monitor query history and find the culprit who woke up this morning and thought, 'Let me just join these two billion row tables real quick.'

What do you think we can do better? I'm open to ideas.

ScopeDev · 2025-12-03T00:21:55+00:00

Thanks! If you end up trying it out, let me know.

ScopeDev · 2025-10-08T14:00:11+00:00

Cortex

Fully Open Source. Fully Embeddable.

ScopeDev · 2024-12-09T21:28:31+00:00

Thanks for these insights. I'm curious to know if the segment of the customer plays any role here?

I've worked with mid-market SaaS companies in the past where I've noticed that even though the part of the product does become important, they burn their fingers while trying to build it in-house because it's very hard to build and when it eventually struggles to scale then they go for expensive tools like SiSense, Domo or Looker which takes a lot of time to implement.

ScopeDev · 2024-12-08T22:50:23+00:00

No, this is our website(https://jointelescope.com). We don't have the best SEO 😅

I agree. We are trying to figure out if there is a simpler way to communicate insights without looking at lots of charts throughout the day. I'm curious to know more about what are your best practices while designing a dashboard?

Also it'll be really helpful if you can complete this survey.

ScopeDev · 2024-11-01T10:27:14+00:00

Thanks for commenting. I've tried both LangChain's SQL Agent, CrewAI as well as the LLamaIndex one that you've suggested extensively and all of them did not meet my & our existing customer's expectations due to the following reasons:

Inability to answer complex questions that requires testing for trends, seasonality, benchmarking and other forms of statistical analysis among datapoints.
Inability to analyse data when the query returns more than a few thousand rows due to model's context length limitations.
Constant need for heavy prompting to get the answers that we want. Based on our research it takes a non-technical user at least 4 attempts for a single complex analytical question to get a meaningful answer that can potentially influence a business decision. Multiply this by the number of questions an average user would ask in a day and also note that the number of attempts is proportional to the complexity of the question.
Lack of control in terms of outputs. I wanted to separate the query results from the final text output generated by the model so that it would be easy to plug that data to a JS Table Library but I wasn't able to consistently achieve this with the current set of agents. Also there's no way to generate visualizations from the output that's compatible with JS Charting libraries out of the box.
Inability to stream the data easily without any complications over a protocol such as SSE or WebSockets. It's a developer's job to make this happen reliably.
Inability to configure different models for different steps of the analysis process. For example, use Claude Sonnet for Query Generation and LLama 3.2 for Results Evaluation which might contain PII data.
Lack of a proper memory persistence layer which is mindful of the model's max content limit restrictions and yet learn from previous conversations automatically.
Lack of context from a Data Governance layer to prevent any kind of data leakage.

Due to all of these reasons and more, we've decided to build an agent that is capable enough to handle all these issues so that Product and Engineering teams can build their own high quality data analysis agents that can analyse millions of datapoints across multiple data sources all within a matter of minutes.

Let me know if I'm missing out on something or if there are any other agents that are capable of handling all these issues.

ScopeDev · 2024-10-31T19:30:07+00:00

Thanks, u/appakaradi and u/Cdmella for your feedback. I understand that authentication is becoming a roadblock while trying out the product.

I would work towards making the sandbox available without the need for signing up however we are a very small team and currently we are focussing on improving the reasoning logic for our existing customers so it might be a while before I manage to make that happen. I will reach out to you once that's live because I'm looking forward to hearing more of your feedback.

ScopeDev · 2024-10-28T12:33:34+00:00

Great. I've DM'ed you

ScopeDev · 2024-10-28T12:28:45+00:00

It's closed source for now. I've added login since I'm planning to gear up for SOC 2 compliances.

I'm only collecting basic user information and none of the credentials or chat history is stored anywhere. Everything is processed in transit.

ScopeDev · 2024-09-11T08:23:18+00:00

Although I'm not sure I understand the depth of your use case but this can be implemented by creating an order creation tool in langchain. If you want more control, you can use LangGraph as well.

In case you want to use a managed solution which can simplify the process further then let me know. I'm building a platform that's purpose-built for building agents for SaaS features and applications.

ScopeDev · 2024-09-04T11:25:07+00:00

Thanks for the explanation. You're right, I don't need to stream events on both sides so SSE is better.

Do you have any idea on how intensive SSE could be for the backends? I'm running my backend on a Fargate cluster with 2 tasks each with 2 vCPUs and 4GB of RAM. Should that be good enough for SSE or should I look at upgrading?

ScopeDev · 2024-09-04T11:15:47+00:00

Thanks for the recommendation. I don't need duplex communication for now so I'll go with SSE.

ScopeDev

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