Alternatives
Products that do what Seemore Data does
40% autonomous cost reduction on Snowflake environments
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2017 · github.com
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2017 · github.com
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How it works (tech stack): -Built entirely with Lovabl.dev (no-code front-end + logic) -ChatGPT / Claude for research and inspiration -Powered by GPT-4 Vision to interpret charts visually -Hosted on Supabase for performance & caching It’s not meant to replace analysts — just to speed up how traders interpret data. I’m a designer exploring AI tools, and this is my first attempt to turn an idea into a functional product. Would love to know what you think.
Oct 2025 · quantify-ai.co
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Hi HN! We are excited to share something we have been building for the last 12 months. Castled is a warehouse-native marketing platform built directly on cloud data warehouses like Snowflake, BigQuery, Redshift, and Postgres. Castled allows you to directly use the customer data in your data warehouse and engage them across different channels like Email, Sms, WhatsApp, push, and In-app - without having to copy the data to another tool. We started our journey by building an open-source Reverse ETL solution to make the warehouse data actionable to marketers. However, after talking to 100s of…
2023 · castled.io
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Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
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2015 · taskpipes.com
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Hey hacker news! I built Melchi, an open-source tool that handles Snowflake to DuckDB replication with proper CDC support. I'd love your feedback on the approach and potential use cases. *Why I built it:* When I worked at Redshift I saw two common scenarios that were painfully difficult to solve: Teams needed to query and join data from other organizations' Snowflake instances with their own data stored in different warehouse types, or they wanted to experiment with different warehouse technologies but the overhead of building and maintaining data pipelines was too high. With DuckDB's…
2024 · github.com
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Hey HN — We're excited to share Trellis — a snowflake for unstructured data. We've built an AI engine that turns unstructured data into structured SQL-format based on the schema you define in natural language. We spent a lot of time building ML infrastructure and realized that most data warehouses and data pipelines are not designed for unstructured data (documents, PDFs, calls). While something like a Vector database and RAG are great at search tasks, they really struggle with aggregation and SQL type queries such as 1. How many emails in the past 6 months contain complaints about the…
2024 · demo.runtrellis.com
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Hi HN, I built SubTrack to help teams find unused SaaS tools and cloud resources before they silently eat into budgets. The motivation came from seeing how hard it is to answer simple questions: – Which SaaS tools are actually used? – Which cloud resources are idle? – What will our end-of-month spend look like? SubTrack connects to tools like AWS, GitHub, Vercel, and others to surface unused resources and cost signals from one place. Recently I added multi-account support, currency localization, and optional AI-based insights to help interpret usage patterns. This is an early-stage project…
Jan 2026 · subtrack.pulseguard.in
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Hi HN, We are launching Denormalized (www.denormalized.io), a serverless real-time data platform built on Kafka and Pinot. We felt a bit burnt out by the sheer developer toil we faced when building application around the real-time data stack and set out to create a platform to allow small teams to be very productive with realtime data without having to glue together an elaborate system to serve real-time as well as time series queries. Here is our motivating post. Would appreciate any and all feedback.
2023 · teamdenormalized.substack.com
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