Alternatives
Products that do what Cube – The Agentic Analytics Platform [video] does
You might know Cube as an open-source semantic layer (https://github.com/cube-js/cube). Started in 2018, now 19K+ stars, 1000+ releases. We kept hitting the same wall: everyone wants AI analytics, but AI without business context hallucinates. The fix is a semantic layer — a model that defines what "revenue" or "churn" actually means. But building one by hand takes weeks. So we built an AI agent that writes the semantic layer itself, then uses it to answer questions and build dashboards with no hallucinations. Connect your data → agent builds the model in seconds → ask…
- 1
- 2
- 3
- 4
- 5
- 6
- 7CJ
Hi everyone! I want to share with you a serverless analytics framework - Cube.js: https://github.com/statsbotco/cubejs-client. I’m one of the authors and would love to hear your thoughts and feedback. Cube.js is an analytics layer for applications. It supplies building blocks to add analytics features into your application. It comes with caching, pre-aggregations and all other stuff you need to handle large data sets. We’re launching public beta today, with open-sourced React client and cloud hosted server. We’re planning to open source server as well, so it could be…
2018
- 8
- 9
- 10CJ
2019 · github.com
- 11
- 12AA
Hi, I’m a cofounder of AstroBee and I wanted to share our work with the community. AstroBee is an automatic semantic layer generator for your business. It brings data together from different locations, storing it either in your data warehouse or in one we host. Then, AstroBee scans your data and models it to create an integrated source of truth (we call it an ontology because it’s structured like Palantir’s ontology). Once you have your source of truth, you can either build applications on top of it, or chat with directly to answer analytics questions. If you don’t like AstroBee’s original…
Oct 2025 · app.astrobee.ai
- 13DO
Hi HN! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
- 14AA
We’ve published a set of open-source reference implementations on how to build production-grade Agentic AI applications on AWS. What’s in the repo: • Agentic RAG, memory, and planning workflows with LangGraph & CrewAI • Strands-based flows with observability using OTEL & Arize • Evaluation with LLM-as-judge and cost/performance regressions • Built with Bedrock, S3, Step Functions, and more GitHub: https://github.com/aws-samples/sample-agentic-frameworks-on-... Would love your thoughts — feedback, issues, and stars welcome!
2025 · github.com
- 15
- 16GA
Hello! Introducing geniusrise, an agent framework and component ecosystem for building AI agent networks that are as flexible as your team. landing page: https://geniusrise.ai (fancy but useless) docs: https://docs.geniusrise.ai (please check this out) github: https://github.com/geniusrise (for dear devs) ## Thought process Since the ChatGPT disruption, I've been pondering on what the tooling layer is going to look like for building LLM-interfacing agents. Saw a plethora of tools coming out as we witness here every week. I'd broadly categorize them into the…
2023 · github.com
- 17SO
hello everyone, my first post! AA here, founder of ⌘ Langbase.com — we are a developer platform for building and scaling serverless AI memory agents. I know surveys can be boring, but this one’s different—it’s interactive! That's very much intentional. My team and I have been up for the last 21 hours putting together this report. This was a looot of work, so I hope y'all like it. Introducing … State of AI Agents 2024 report On Langbase, we processed 184 billion tokens and handled 786 million AI agent runs from 36K developers. From all that data plus insights from 3.4K builders who filled out…
2024 · langbase.com
- 18FA
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
- 19FA
Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…
Jan 2026 · marketplace.visualstudio.com
- 20BA
Hey HN, For the last couple of months, we have been building an AI agent for continuous statistical analysis, and we're looking for feedback while it's still early in development. We call it BIGWIG - an autonomous agent that is specialised, and very good at, performing advanced statistical analysis, through long traces of iteration and reasoning. As it builds statistical models it also "emits" outputs back to the user that you can then interact with, iterate on and schedule for follow up analysis. While we're still in BETA, we've launched a public analysis site that showcases some of the…
2025 · askbigwig.com
- 21LA
Hi HN, I’m Harrison, co-founder of Listed. Today we're launching our agentic platform to help your business win in the new age of AI. You can try the platform here: https://getlisted.ai And watch the launch video here: https://www.youtube.com/watch?v=MJUPo6H78z8 The idea for this came from pure frustration. I asked ChatGPT about my own company and it hallucinated, inventing features and getting basic facts wrong. I realized there was no mechanism for a business to provide a verified source of truth to these models. This problem is now existential. With Google's AI…
2025
- 22WB
Humans compete to improve their AI agents on benchmarks. But what if agents could collaborate and compete on their own? We built Hive, a crowdsourced platform where agents can evolve solutions together. One agent begins to tackle a task, iteratively improving its code. Then other agents join. They read each other’s runs, fork the best ideas, propose new ones, and push the solution forward together. We already have agents working on benchmarks like Tau2-Bench, Terminal-Bench, and ARC-AGI-2, with more tasks coming soon. We also support the new OpenAI Parameter Golf Challenge, and you can…
Mar 2026 · hive.rllm-project.com
- 23DR
The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
2025 · github.com
- 24RA
Hi HN! Sean from MindStudio here. I wanted to share something we've been working on that I think introduces some new ideas into the "AI coding agent" space. Remy is an AI agent that builds full-stack TypeScript apps from a spec written in a new flavor of annotated markdown. The spec has two layers: prose describing what the app does, and annotations that carry the technical precision (data types, edge cases, validation rules, code snippets). The agent then "compiles" this into code: backend methods, typed schemas, frontends, test scenarios, and everything else are derived artifacts of the…
Apr 2026 · remy.msagent.ai
Ranked by how close each launch is in meaning, then by votes. Refine with a description →