Engraph – Automated ETL Pipelines
Hey HN, we’re Ross and Javier, co-founders of Engraph (www.engraph.ai). Our goal is to completely automate the process of building ETL pipelines, from ad hoc pipelines for question answering to fully fledged ETL pipelines within large organisations: For ad hoc pipelines, a question answering platform which enables users to ask questions in natural language about their organisation's data. Traditionally, access to data within organisations is limited to a handful of data-engineers. This means that if an employee needs access to some data, they have to go through a lengthy process of…
Engraph – Automated ETL Pipelines launched on March 15, 2023 with 5 votes, #2,445 of 5,007 launches that month and more than 50% of that year's launches.
What it does
In the maker’s words, at launch
Hey HN, we’re Ross and Javier, co-founders of Engraph (www.engraph.ai). Our goal is to completely automate the process of building ETL pipelines, from ad hoc pipelines for question answering to fully fledged ETL pipelines within large organisations: For ad hoc pipelines, a question answering platform which enables…
Does a similar job
all alternatives →
Demystifying Advanced RAG Pipelines2023 · github.com · ▲131I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
Pipelex – Declarative language for repeatable AI workflowsOct 2025 · github.com · ▲122We’re Robin, Louis, and Thomas. Pipelex is a DSL and a Python runtime for repeatable AI workflows. Think Dockerfile/SQL for multi-step LLM pipelines: you declare steps and interfaces; any model/provider can fill them. Why this instead of yet another workflow builder? - Declarative, not glue code: you state what to do; the runtime figures out how. - Agent-first: each step carries natural-language context (purpose, inputs/outputs with meaning) so LLMs can follow, audit, and optimize. Our MCP server enables agents to run pipelines but also to build new pipelines on demand. - Open…
Flow – A dynamic task engine for building AI agents2024 · github.com · ▲160I think graph is a wrong abstraction for building AI agents. Just look at how incredibly hard it is to make routing using LangGraph - conditional edges are a mess. I built Laminar Flow to solve a common frustration with traditional workflow engines - the rigid need to predefine all node connections. Instead of static DAGs, Flow uses a dynamic task queue system that lets workflows evolve at runtime. Flow is built on 3 core principles: * Concurrent Execution - Tasks run in parallel automatically * Dynamic Scheduling - Tasks can schedule new tasks at runtime * Smart Dependencies - Tasks can…
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 20d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 29d ago · world.pixverse.video
Source: Show HN post ↗ · launch text quoted in part
Launched alongside, March 2023
the whole month →
Typing Mind▲826Chat with AI using your API keys. Pay only for what you use. ChatGPT, Gemini, Claude, and other LLMs supported. The best chat LLM frontend UI for all AI models.
AI · 2023 · typingmind.com
Sequoia▲726Personalized men's sexual health with on-demand experts
Life & fun · 2023 · sequoia.health
- BI
I'm a big fan of the BBC podcast In Our Time -- and (like most people) I've been playing with the OpenAI APIs. In Our Time has almost 1,000 episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all still available, so it's my starting point to learn about most topics. But it's not well organised. So here are the episodes sorted by library code. It's fun to explore. Web scraping is usually pretty tedious, but I found that I could send the minimised HTML to GPT-3 and get (almost) perfect JSON back: the prompt includes the Typescript definition. At the same time I…
AI · 2023 · genmon.github.io