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Show HN: Sourcetable – AI Spreadsheet and Data Platform

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Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#22

It’s amazing that Microsoft - given their focus on AI and decades of experience in spreadsheets - doesn’t offer this type of functionality. Corporate bureaucracy vs startup agility!

At risk of poking the bear, they should have done this decades ago. Except for LLMs they have had everything they needed to bundle this stack into a single product solution; this would be much better for users.

And yes! We're definitely of the opinion that as a startup we can outcompete the two trillion-dollar death stars when it comes to product experience. AI is a platform shift!

Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#23
post #20

Awesome, have you got any mining specific worked examples or spatial examples? Thinking about lidar point clouds and running deltas for stock pile management. Looking at building a new mine and typically there at any mine site there are excel macros which might take an hour to run embeded in the operations. Often developed by older engineers, who will default to excel. Any suggestions on how best drive technical user…

Yes actually! My cousin is a mining engineer so I spent a bunch of time playing around with mining data during testing. Turns out all New South Wales government data is public. Right now you can talk to any CSV or database using LLMs. I've also played around with a bunch of marine biology datasets too!

(p.s. I think Andrew, CTO, is going to jump in here as he has more experience in this space.)

Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#24
post #23
post #20

Awesome, have you got any mining specific worked examples or spatial examples? Thinking about lidar point clouds and running deltas for stock pile management. Looking at building a new mine and typically there at any mine site there are excel macros which might take an hour to run embeded in the operations. Often developed by older engineers, who will default to excel. Any suggestions on how best drive technical user…

Yes actually! My cousin is a mining engineer so I spent a bunch of time playing around with mining data during testing. Turns out all New South Wales government data is public. Right now you can talk to any CSV or database using LLMs. I've also played around with a bunch of marine biology datasets too! (p.s. I think Andrew, CTO, is going to jump in here as he has more experience in this space.)

Can you email me -- eoin@sourcetable.com -- more about the Excel macros? This might be easy to help you out with agents. A lot of compute-intensive stuff that takes ages in Excel is nearly instant in Sourcetable because we are leveraging cloud compute, but it really depends on your use case.

Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#25
post #20

Awesome, have you got any mining specific worked examples or spatial examples? Thinking about lidar point clouds and running deltas for stock pile management. Looking at building a new mine and typically there at any mine site there are excel macros which might take an hour to run embeded in the operations. Often developed by older engineers, who will default to excel. Any suggestions on how best drive technical user…

The underlying datatypes we support in our data-warehouse support 3d and 4d data. So we can do vector queries on these and do transformations over different spaces. I think given what you need we can put your data in our data-warehouse, and then present it to the older engineers in an excel format with 3d plotting. We might want to chat about the details though, give me a holler at andrew@sourcetable.com

Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#26
Interesting. I think you're on to something here. I fully agree that a combination of spreadsheets and SQL are the ideal tools for data analysis -- not a SaaS GUI.

> Niching down, if you work in operations at a With the rise of AI, companies like Tembo that help you set up all in one databases, and tools like this, I'm increasingly of the mind that many companies should start bringing things like analytics and observability in-house. I don't see the need to pay Mixpanel or Datadog thousands of dollars per month when a self-serve solution that relies on tried and true tech is more or less at your fingertips.

Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#28

Interesting. I think you're on to something here. I fully agree that a combination of spreadsheets and SQL are the ideal tools for data analysis -- not a SaaS GUI. > Niching down, if you work in operations at a With the rise of AI, companies like Tembo that help you set up all in one databases, and tools like this, I'm increasingly of the mind that many companies should start bringing things like analytics and observ…

Agree. A general thesis I have is that the API-ification of the web fragmented business information, and with every new SaaS tool we fragment our company's data further. The trend at all company sizes is to be increasingly analytical, but for SMBs it's too hard to get access to your data (mainly due to technical limitations). So it makes sense to centralize data somewhere, and we think that somewhere is inside the data tool that everyone actually uses: the spreadsheet.

Many other advantages of this data centralization too. Data + spreadsheets + compute is a nice application base for agents.

Re: Show HN: Sourcetable – AI Spreadsheet and Data Platform

#29

What external checks are included to verify the chatbot output?

Wherever possible, the chatbot output is deterministic, in that to answer a query, we're realtime generating and running code or SQL against your data. Our LLM orchestrates that, and finally evaluates whether the output correctly and adequately answers the question.

We also extensively use synthetic data and examples to guide and constrain our models.

Another way we're ensuring good-quality output is to ensure good-quality _input_ -- by enriching the detail and specificity of the user's question, and asking the user to disambiguate when we determine the question is too broad.

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