... data either meant fighting ad-hoc Python scripts, or losing track of exactly what happened to the data along the way. So we built something that handles the cleaning/transformation without code, connects directly to Postgres, MySQL, MongoDB, Snowflake, and Databricks, and the part we actually cared about logs every single operation and parameter so a run is fully reproducible and auditable later. Pipelines and trained models can be reused on new datasets instead of rebuilt each time ...

... minute flow works (the user's journey): 1. Connect (30s) - User links a source: uploads a CSV/Excel, or connects a database, Google Sheet, Stripe, etc. 2. Understand (30s) - Your system profiles the data automatically: detects column types, dates, metrics vs. dimensions, and relationships. This is the step that makes the rest automatic. 3. Generate (45s) - It picks the right visualizations (trends over time, top categories, distributions, KPIs) and lays them out into a coherent dashboard - not just random charts ... ... churn spiked in week 3." The magic isn't just charts - it's that the user gets answers, not a blank canvas. Why it's compelling - It removes the hardest step. Most BI tools (Tableau, Power BI, even Databricks

... data can stop playing detective and start deciding. What it is: a single, clean data layer that connects CRMs, finance tools, and ops systems so revenue, finance, and ops teams stop arguing over whose numbers are right. Not a Databricks or Fabric replacement. A layer above them, built for mid-market teams those platforms were never designed for. Where I'm at: Launched publicly April 13 6 beta testers Website traffic 12 to 52 visitors in 4 days Not looking ...

... tailors a few projects for you to reach the similar position, we have had 1500+ engineers on our platform from people working as quants in Jane Street, Citadel, IMC Trading, Graviton, Optiver to software companies like Google, Amazon, Uber, Databricks, Snowflake, Twilio, Confluent, Rippling. We even have some researchers from Google Deepmind, Anthropic and other frontier AI labs, you can all get to know what you need to do to your profile to reach where they are. Obviously your context ...

... past few months, with huge progress since 2024. Tower now connects directly to your data, automatically builds semantics, transformations, and dashboards, and generates actionable insights in minutes. New in 2025.10: Tower Pipelines: Combine multiple sources (HubSpot, Snowflake, Airtable, Excel, Databricks, MS SQL, Tally Prime, and more) without a separate ETL tool Tablet Apps: AI-native dashboards for iOS & Android Smarter AI analytics & new connectors Intelligent data transforms Tons of performance and UI/UX improvements Question: If your dashboards could ...

... Nika(@busmark_w_nika): @atique_bandukwala1  I think that you are already investing in it :D what about other companies? Comment from Nika(@busmark_w_nika): @elenamira  What about Lovable? Why did you choose Vercel over other competitors of this tool? Comment from Nika(@busmark_w_nika): @chilarai  There s no better way to support your favorite products. I usually like to invest in the stocks of companies whose products I use. Comment from Nika(@busmark ... ... speed that AI has been developing, that's quite a long time ago. Since then, GPT-4o was simply a slight optimization on GPT-4. GPT-5's been underwhelming. Meanwhile, at least in terms of model performance, their competitors

... from Attila B g zi(@attila_bogozi): @d_ferencha  probably right, they've created a very well structured digital ecosystem to support that. Go Estonia! Comment from Adam Lababidi(@adam_lab): @busmark_w_nika  Lovable, Spotify, Sana, Voi, Klarna, databricks and soon Migma.ai Comment from D. Ferencha(@d_ferencha): @busmark_w_nika  Bolt, Wise, Pipedrive Comment from Adam Lababidi(@adam_lab): Definitely Stockholm Comment from vivek sharma(@vivek_sharma_25): Europe s startup geography is shifting fast. London still ...

... recently came across some news: Claude for Financial Services officially launched in mid-July. It s designed specifically for the finance industry, integrating data from platforms like PitchBook, Morningstar, Snowflake, S&P Global, and Databricks to support market research, due diligence, and investment decisions. During early testing, Claude Opus 4 hit 83% accuracy on complex Excel tasks. It really makes me question how much room there is left for AI Agent startups ----LLMs are getting better at handling more ...

... DataBricks just announced acquiring @Neon for $1B source: TechCrunch How do you feel about this announcement? Would you keep using it or migrate to an alternative