[HN Gopher] Show HN: Sourcetable - AI Spreadsheet and Data Platform
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Show HN: Sourcetable - AI Spreadsheet and Data Platform
Hi HN! I'm Eoin, founder of Sourcetable (https://sourcetable.com).
Sourcetable is an AI-native spreadsheet that syncs with all your
data. Users pair with an AI copilot that helps them do their
spreadsheet work, as well as more database-centric analysis and
SQL. Soucetable syncs with databases including Postgres, MySQL,
and MongoDB, and over 100+ business applications including Stripe,
Zendesk, Hubspot, Quickbooks and Google Analytics. That data is
available in a spreadsheet, and any models you build automatically
update in near-real-time as new data flows in. The core primitives
are AI + spreadsheet + data sync + storage + compute. If you want
to play with Sourcetable today, the easiest way is to upload a CSV
and start asking questions. Who is it for? Sourcetable is for
analysts, operators and finance folk doing data-centric work in a
spreadsheet. Sourcetable's spreadsheet-based AI assistant
understands workbook range selection and can adjust scope context
to the datasets you are working with. You can talk directly to your
database and SaaS integrations, which is great for analysis, data
search and retrieval, SQL writing & editing (including writing
joins across different datasets), and automatic chart creation.
Niching down, if you work in operations at a <50 person startup or
SMB and your company relies on a Postgres or MySQL database,
Sourcetable is an affordable reporting tool with turnkey data
infrastructure that doesn't require code or engineers to set up.
Spreadsheets are the most used analytical tool on the planet. AI is
a platform shift with broad applications. We are staying open-
minded about users and use cases since everything is so new.
Backstory: I spent ten years working in de-facto operations and
technical roles at startups. Sourcetable draws from that experience
of needing better data tooling inside spreadsheets, and constantly
hacking ad hoc solutions to fill the gap. Andrew (CTO / co-founder)
previously had a deep learning company and was initially drawn to
the idea that Sourcetable could be an operating system for the web.
We're both Aussie expats in the Bay Area, which is how we met.
Internally, we think of Sourcetable as an application platform,
with AI applications being a useful and interesting place to focus.
Features & Use Cases: Talk to your CSV files, spreadsheets,
integrations, and datasets using LLMs. AI + data work: Text-to-SQL,
search and retrieval from databases, LLM-based data analysis. (This
is an entirely different experience to what Copilot/Gemini &
Excel/Sheets provide, since they are thin workbooks and not data
platforms.) AI + spreadsheet work: formula assist, workbook
analysis, data cleaning, chart creation, error handling,
summarization, chat, etc. Automated reporting: data is synced,
reports you build stay up to date. No-code data access: give the
business team safe database access so they will leave you alone!
Centralizing data for cross-channel reporting. (e.g. Postgres +
Stripe + Mailchimp) Analyzing large CSV files: Sourcetable can
handle multi-gigabit files. (Google Sheets can't handle large data
and the experience in Excel is rather cumbersome.) Technical
Details: Sourcetable was built to be fast. It was also built to
scale. AI: LLama 3 (via Groq), Claude, GPT-4o, LiteLLM, custom
LLMs Frontend: DuckDB, React, ShadCN, AntV / Bizcharts, Plotly,
CodeMirror, Hookstate Backend: DuckDB, Python, Cassandra, Redis,
NGINX, Cloudflare Data Eng & Transformations: Fivetran, DBT,
Apache Arrow, SQLglot Distributed Computing & Scaling: Daft, Ray,
Cloud Formation Other: Linux Namespaces, Dill (U.Queensland) A
huge thank you to the open source community, and a special shout-
out to DuckDB for being so damn fast. Thank you also to Groq &
Anthropic for the rate limit increases in time for this ShowHN
post! - Feedback: Product feedback is welcome!
eoin@sourcetable.com
Author : mceoin
Score : 144 points
Date : 2024-09-19 11:28 UTC (1 days ago)
| yawnxyz wrote:
| > Niching down, if you work in operations at a <50 person startup
| or SMB and your company relies on a Postgres or MySQL database,
| Sourcetable is an affordable reporting tool with turnkey data
| infrastructure that doesn't require code or engineers to set up.
|
| I'm already using Retool for these kinds of tasks- what does
| sourcetable do that I can't already do with Retool?
|
| edit: also, did you build your own spreadsheet engine, or use an
| off-the-shelf one? (also will it be open source ;P)
| mceoin wrote:
| Category Comparison (table-based solutions): "How are you
| different than Retool/Airtable/Coda/Notion/Zapier Tables, etc."
|
| The primary difference vs table-based solutions is that
| Sourcetable is a spreadsheet in the common sense of the word,
| similar to Excel and Sheets. We have A1 notation and cell-based
| referencing. This is what most users expect, and this
| flexibility/familiarity has a big impact on the breadth of
| users and use cases within a team.
|
| The formula referencing system of these table-based solutions
| is usually very limited both to columns/rows (not cells), and
| is a set of SQL-based queries which are much more limited than
| that 500+ formulas and functions spreadsheet users commonly
| expect.
|
| Retool specifically: I tend to think of Retool as a lightweight
| custom-ERP software system, whereas Sourcetable more like Excel
| + PowerBI + Data Warehouse, so we will generally be much
| stronger for reporting and analysis. We definitely have some
| overlap in potential users since technical operators should
| like us both. FWIW - Retool is an excellent product.
| dioptre wrote:
| Hi I'm Andy, Cofounder & CTO @ Sourcetable.
|
| We use a heavily modified licensed engine that prevents us from
| open sourcing everything (for now). We have plans to open
| source our agentic/plugin framework, and other parts of the
| system. We also have a strong ethos of contributing back to
| open source where we can (contributed back to Arrow, DuckDB
| etc.).
|
| I'd also add that while everyone knows how to use and work with
| spreadsheets, we also provide a SQL layer on top that you can
| use to query data sources as an advanced user (we developed a
| nomenclature to work within sheets/across sheets/files/our
| data-warehouse). This allows more technical users to work side-
| by-side in the same environment as non-technical users without
| crossing pythonic or reporting boundaries.
|
| On top of this, the AI assistant can answer most of the
| questions you might have of all this data.
|
| I think as ML gets more sophisticated, we will in general need
| to be less technical. The "tooling" might even disappear, but
| we will still need something to communicate important data
| centric decisions. Whether you like it or not spreadsheets are
| the foundation of human research and operations and have been
| for thousands of years, and I feel humanity will need less
| complicated "tools" and we will keep to our roots.
| Jayakumark wrote:
| Will you be able to share name of the engine ?
| codegladiator wrote:
| Seems like customized version of luckysheet
|
| https://dream-num.github.io/LuckysheetDemo/
|
| https://github.com/dream-num/Luckysheet/issues/1454
|
| I am not related to either sourcetable or luckysheet
| mmerlin wrote:
| or possibly FortuneSheet which is an actively maintained
| fork of the original LuckySheet
|
| https://github.com/ruilisi/fortune-sheet
| escot wrote:
| Very cool. It would be great to have auto complete across cells.
| mceoin wrote:
| Yes we don't yet have the full auto-suggest magic that Sheets
| offers, but you can click-drag for auto-complete the same way
| Excel offers.
|
| We released Sourcetable today with the AI chatbot & AI data
| analysis features, but a very limited cell-based AI (only
| "summarize" and "fix formula"). We'll be releasing a big AI-
| based magic-autofill solution in the coming weeks.
| sim_123 wrote:
| This is amazing. I've been scouting for such a solution as we've
| outgrown excel. Giving it a spin
| mceoin wrote:
| A very common use case we see is SMBs having outgrown their
| spreadsheet but not wanting to move to a full-blown BI tool.
| They want the power, but not the change in interface/medium.
|
| I didn't go into details above but a nice thing is that we
| leverage cloud compute and storage, so you can query billion-
| row data in sub-second time. (Courtesy of Duck!)
| _hfqa wrote:
| Congrats on the launch! It's wild to see AI stepping into
| spreadsheets like this. Pretty soon there won't be a part of our
| workflow AI hasn't touched.
| mceoin wrote:
| Thanks _hfqa! We think there's massive potential here. It's a
| big platform shift, and spreadsheets weren't really impacted by
| the mobile or cloud compute waves, so it's a space long-overdue
| for disruption. (The last shift was back when Google Sheets
| took spreadsheets to the browser 17 years ago!!)
| alooPotato wrote:
| Cool.
|
| How did you build so many integrations so fast?
|
| Selfishly, would love to see Streak (CRM) integration as well.
| mceoin wrote:
| Mostly Fivetran, a little Airbyte, and a few custom
| integrations. Would love to add Streak (can you get it into
| Fivetran? We can usually crank those integrations out within an
| hour.)
| mceoin wrote:
| p.s. I was a massive Streak user at a previous (sales-driven)
| startup. Big fan!
| hisnameisjimmy wrote:
| Fivetran will build a Streak integration if you bring a
| customer who will use it (sometimes as little as one):
| https://fivetran.com/docs/by-request-program
| aerosmile wrote:
| 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!
| mceoin wrote:
| 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!
| luke-stanley wrote:
| Actually Microsoft do now have Copilot and Python in Excel
| recently released last week. Maybe a bit slow.
| mceoin wrote:
| Platform wise, the equivalent would be if they combined
| Excel, PowerBI, Data Factory and Azure into a single tool.
|
| Technically you _can_ combine these, but it's a cumbersome
| experience and difficult for most people. Vertically
| integrating their equivalents simplifies things a lot.
|
| (Small note: we don't currently offer Python to users but
| likely will at some point)
| temac wrote:
| I dont know if the Python in Excel architecture as changed
| but last time i saw it, it was insane and unusable for me
| (data sent to MS servers where a linux container executes
| python: you need both a subscription and that the data in
| question not be regulated)
| djbiggs wrote:
| 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 adoption (asides
| from dropping it on the kids in the engineering deparments, can't
| wait that long) ?
| mceoin wrote:
| 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.)
| mceoin wrote:
| 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.
| dioptre wrote:
| 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
| petergreen wrote:
| great product. congrats on the launch
| dioptre wrote:
| Thank you!
| mmckelvy wrote:
| 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 <50 person startup
| or SMB and your company relies on a Postgres or MySQL database,
| Sourcetable is an affordable reporting tool with turnkey data
| infrastructure that doesn't require code or engineers to set up.
|
| 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.
| mceoin wrote:
| 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.
| threeseed wrote:
| > So it makes sense to centralize data somewhere
|
| Modelling and integrating datasets that you don't own is
| extremely hard.
|
| Shopify for example updates their API every 3 months.
|
| How much time and money do you think an SMB can afford to
| spend on this before the ROI becomes so poor that they
| abandon it entirely.
| mceoin wrote:
| Yes some integrations are excellent (hey Stripe : ), some
| are terrible (no comment on who). We're finding that LLMs
| increasingly able to fill the gap around organizing data
| schema for that initial data prep piece where someone has
| to build the data tables that others consume. To your
| specific question/problem set, when a schema updates you
| end up with a "fuzzy schema matching problem"; we are
| solving that separately anyways for a separate product
| feature requirement.
|
| Strong note here that the current state of technology is
| _much_ better for SMB scale data and not enterprise scale
| data with messy schemas.
| mceoin wrote:
| There is a separate answer here which is many (most?) SMBs
| can't afford technical folk, so the ability integrate data
| _at all_ , talk to it and model it (using SQL or AI), is
| already a big step forward for them.
|
| My personal use case tends to involve a lot of Postgres
| data and transaction events for my reporting. We see
| "simple" businesses like parts manufacturers, print shops,
| vineyards, etc. all doing something similar.
| threeseed wrote:
| Minus the AI part tools like this have existed for decades.
|
| And companies are not dumping their SaaS tools and switching to
| them en masse.
|
| Because (a) data silos have dramatically increased pushing
| dreams of a unified data schema out of reach, (b) technology
| stacks have become far more complex necessitating tools like
| Datadog and (c) competition is stronger than ever meaning that
| skimping on paying for tools like MixPanel is often short
| sighted and counter productive.
|
| Companies like this will do fine and there will be always be a
| demand for them especially in the SMB space. But there simply
| isn't the business value in bringing a lot of analytics and
| observability in-house in almost all cases.
| mmckelvy wrote:
| Not yet. But in the analytics case, suppose you could build a
| tool that collected data on your own infrastructure, allowed
| you to write plain SQL against a PostgreSQL database to get
| whatever analytics data you need, had an AI-driven text-to-
| SQL option so non-technical users could get whatever
| analytics data _they_ need, and output everything to a
| universal interface, i.e. a spreadsheet? No vendor flavored
| DSL, GUI, or workflows to learn. That product would be tough
| to beat. It wasn't built in the past because it was hard. But
| with AI and something like Tembo or Timescale, is it actually
| hard anymore?
| theGnuMe wrote:
| Managed services are useful.
| HeralFacker wrote:
| What external checks are included to verify the chatbot output?
| SoulAuctioneer wrote:
| 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.
| SMAAART wrote:
| Looks interesting, commenting so that I can remember.
| sammysidhu wrote:
| Congrats on the launch! It's been great working with you from the
| Daft side
| dioptre wrote:
| Thanks mate!
| smcleod wrote:
| Are you open sourcing the product for non-commercial use?
| mceoin wrote:
| Would love to but unfortunately there are pieces we can't open-
| source for various reasons. We'll open source bits and pieces
| over time, and generally are excited to start blogging about AI
| & technical learnings now that the product is out of stealth
| mode.
|
| Small plug for the analytics tracker we are using which Andrew
| (CTO) built and is open source:
| https://github.com/sfproductlabs/tracker
| mg1973 wrote:
| Brilliant work team, great to see this being launched.
| dioptre wrote:
| Thank you!
| Brajeshwar wrote:
| You might want to check who is blacklisting you and request to
| unblock. AdGuard blocked sourcetable.com as "Scam".
|
| https://www.dropbox.com/scl/fi/np92pyo0eb0zphysc9wwz/screens...
| SoulAuctioneer wrote:
| Thanks for reporting! Taking a look now.
| dioptre wrote:
| Hey do you mind removing this comment? Seems it might have
| caused us to be blacklisted?
| Brajeshwar wrote:
| I'm sorry, I've missed the "delete" window. But may I know
| how a comment here (after it being blacklisted) about it
| being blacklisted will be the reason to be blacklisted?
| mceoin wrote:
| -\\_(tsu)_/- deciphering magic algorithms.
|
| Very much appreciate the bug report. Thank you!
| halfcat wrote:
| I always wonder where these spreadsheet/database apps will land.
| Usually it falls flat for one of a few reasons I've observed:
|
| - Fundamental gap in skillset, in that if you want to have
| ultimate flexibility to slice and dice the data and report on
| whatever you're seeking, you've ultimately needed SQL skills in
| the past (which isn't rocket science, but also isn't something
| most accounting users can run with on their own).
|
| - Fundamental desire of users to work with unstructured data.
| This goes back at least as far as Excel vs Lotus Improv in the
| early 90's. Joel Spolsky talked about this, how they were
| terrified that Lotus Improv was going to kill Excel, because
| Improv was built to work with structured data, which users could
| then query and ask questions of to get any answer they want. But
| it turned out, as they observed people using both apps, there
| were zero users that used 100% normalized, structure data.
|
| - Imperfect translation between spreadsheet and database. I've
| seen these work well 99.9% of the time, but at some point a
| column gets added or something that throws off formulas. And 0.1%
| error is basically catastrophic in accounting.
|
| Maybe LLMs help overcome these challenges. Wish you luck.
| mceoin wrote:
| This is 100% the correct insight in my experience.
|
| TL;DR, most technical people massively overestimate the
| technical / data abilities of regular spreadsheet users. We
| find simple use cases are best, and with each new LLM release
| the UX around more complex data improves significantly.
|
| The reason we chose to build as a full-blown spreadsheet
| instead of just a table-based solution was that we saw that
| most people want the flexibility of a regular spreadsheet, but
| access to their (structured) business data. Table-based
| solutions wedge you into AI and you can never get out of that.
| SoulAuctioneer wrote:
| Agree with you, and we're definitely trying to thread the
| needle!
|
| We're generating the SQL to answer natural language questions,
| so folks can just get answers and results tables if that's all
| they need, with the option for power users to fiddle with the
| SQL either directly or via a query editor GUI.
|
| There's a ton of use cases for working with unstructured and
| semi-structured data and that's coming down the pipe!
| primitivesuave wrote:
| This is incredible. I uploaded a CSV with ~6000 rows containing
| campaign finance data for a particularly corrupt local politician
| and asked "what was the total contributed amount in [year]". Not
| only did it produce the correct answer (in around the same amount
| of time it took me to calculate it on my end) but it also seemed
| to understand that the spreadsheet was related to campaign
| finance in the "summary" portion of the response.
|
| The most useful aspect was that I could ask "what was the total
| contributed amount between January and June of 2020" and get an
| accurate answer for that as well. Since the date column is
| provided as an "MM/DD/YYYY" string, I would normally have to do
| some boilerplate work to sanitize this.
|
| For my particular use case, the charting aspect left a few things
| to be desired - once I grouped campaign donations by contributor,
| I could only see the first 10 rows in the AI response, with no
| option to expand the output. But overall I was truly blown away
| that something like this is even possible for a small team to
| build.
| mceoin wrote:
| > For my particular use case, the charting aspect left a few
| things to be desired - once I grouped campaign donations by
| contributor, I could only see the first 10 rows in the AI
| response, with no option to expand the output.
|
| Insert it as a table on the page (you should see a button), it
| will then print the whole table result from that query into the
| spreadsheet. Also, you can check the SQL first and validate it,
| then print to table after that.
|
| Try a few million rows and see what happens!
| dioptre wrote:
| Also keep an eye out on the limit - we default to 10,000 to
| keep it snappy but if you want to make it larger its a click
| away. The "summarize table" button should auto limit to 1B+
| rows.
| jadbox wrote:
| Can Office 365 Copilot do this too?
| dioptre wrote:
| We are a generally a generation ahead of sheets and excel.
| You might be able to do some of the things in the older
| software but it won't be a button press. The ability for you
| to run data queries (and let the AI do it for you) next to
| the traditional A1 notation we invented.
| samymov wrote:
| Huge congrats on the Launch ! You guys crushed it with all the
| thought and hustle behind creating such a valuable tool. Wishing
| you nothing but success on the ride ahead!
| dioptre wrote:
| Thankyou!!!
| longstaff2009 wrote:
| Thats a spicy example dataset!
|
| I like that it's able to infer information from the context of
| the cells, e.g. being able to run a query across continents when
| the data only contains the country.
|
| Being able to ask it to interpret the results is helpful, it
| would be cool if it automatically told you if there was enough
| data to have statistical significance in the conclusions it was
| presenting.
| mceoin wrote:
| You may see that we try to suggest follow-up questions or
| question improvements where we think better context-in will
| result in a better result-out.
|
| Curious what will happen if you modify the question to be more
| explicit?
|
| I have seen that PMs and data-trained folk tend to be very
| articulate in asking for _exactly what they want_ and that
| tends to lead to significantly better LLM responses.
| topicseed wrote:
| An improved and more interactive version of Google Sheets'
| explore tab. Looks good!
| jacobjellyfish wrote:
| This looks great! Well done. My concern is that there's not a
| single mention of data privacy. Which is is a red flag for any
| one coming from an enterprise world. Get that sorted and I'd
| consider using your tool for actual work.
| mceoin wrote:
| Hi - we encrypt everything at rest and use metadata to improve
| LLM performance.
|
| We don't yet have enterprise-grade data permissioning or
| compliance certificates like Soc2. Those will come in time.
| zeptian wrote:
| very nice app. just the front-end browser component alone is
| super-slick. but expecting users to bring their data to your
| platform is a barrier to adoption.
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