AI · alternatives · 2026
24 alternatives to Carbon
The analytics layer of AI
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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Build the semantic layer that makes AI analytics trustworthy
Mar 2026 · metabase.com · its alternatives →
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Track your AI spend and connect it to business outcomes
Aug 2026 · rippling.com · its alternatives →
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The New Waydev▲299Measure the full AI SDLC. From token to production.
Apr 2026 · waydev.co · its alternatives →
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Build AI models and get predictions, no code required
2023 · mentana.ai · its alternatives →
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Diamond▲168Graphite's agentic AI-powered code review companion
2025 · graphite.com · its alternatives →
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Depthdata▲154The system of analyze your company's AI usage
Jul 2026 · depthdata.app · its alternatives →
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Hey, I'm Marc one of the co-founders of Fabi! We've all seen the "chat with your data" or the "AI-as-an-assistant" when building reports, but we felt like this wasn't quite right. So we decided to build a system that allowed users to: * Connect any data source to the AI * Purely chat with the AI and their data (so we show the output right in the chat before you even apply the changes) * Convert that chat to a repeatable analysis with a data app or workflow * Toggle back to chat mode without missing a beat Basically this means that if you're a data person, you don't have to go through these…
2025 · fabi.ai · its alternatives →
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CrbonFree▲61Audit-grade carbon numbers for every AI token you use
27d ago · crbonfree.com · its alternatives →
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…
May 2026 · github.com · its alternatives →
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Measure the carbon footprint of transaction data
2021 · carboninterface.com · its alternatives →
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I started leaning in on AI heavily this year, as I wanted to get more done autonomously, but then my token usage climbed dramatically to the point where my weekly quota would run out before the end of the week, sometimes a couple of days into the week. I realised I had to do something about it else I'd have to double my spend. So I decided to start tracking my cost per task type. This revealed that a lot of my spend went to searches/scans or simple things like scouting tasks. I then decided to turn this into a simple CLI tool that can be used to read your OpenAI-style logs locally, and…
Jul 2026 · github.com · its alternatives →
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
2025 · github.com · its alternatives →
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai · its alternatives →
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Afford AI▲11Track LLM usage, costs & tokens with real-time insights.
2025 · affordai.io · its alternatives →
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Hi HN, There’s been a lot of discussion lately around context graphs, decision traces, and how AI systems reason. One thing we kept running into: when AI agents make real decisions, the why behind those decisions often disappears. The context is scattered across prompts, tools, policies, and approvals. Logs show what happened, but not why it was allowed. TraceMem is an attempt to make decision context durable. It records the reasoning, authority, and context behind AI actions as a system of record, not as monitoring data, but as memory. Happy to share more details or answer questions. - Tommi
Jan 2026 · tracemem.com · its alternatives →
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Smarter Data Insights with Conversational AI
Oct 2025 · lumenore.com · its alternatives →
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Engineering and product writing from the team building Cube, the agentic analytics platform built on a semantic layer.
2022 · narrative.bi · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →