Clusy vs Hex
These two are often shortlisted together but aim at different jobs. Hex is a polished analytics workspace where data teams build SQL-and-Python notebooks and publish them as apps for stakeholders. Clusy is an agent-native notebook where ML work — training, fine-tuning, evaluation — gets done end to end on real GPUs.
At a glance
| Clusy | Hex | |
|---|---|---|
| Built for | ML researchers and data scientists running experiments | Data and analytics teams answering business questions |
| Center of gravity | The experiment: train, fine-tune, evaluate, branch, compare | The warehouse: SQL + Python analyses published as apps |
| AI | Agent executes whole workflows end to end; you pick the model | Notebook Agent and Magic AI assist with queries, code, and analyses |
| Compute | Managed GPU sandboxes included, free 8 vCPU / 8 GB RAM CPU sandbox up to H100 / H200 | Warehouse pushdown plus hosted Python — GPUs aren't the focus |
| Experiments | Native notebook branching with side-by-side comparison | Version history and review flows oriented at collaboration |
| Output | Notebooks, trained models, evaluations, shareable results | Interactive data apps, dashboards, and threads for stakeholders |
| Cost | Free plan; flat monthly plans from $30 with usage allowances | Free tier for individuals; team and enterprise plans priced per seat |
The core difference
Hex is warehouse-first. Its center of gravity is the modern data stack: SQL cells against Snowflake or BigQuery, Python for the last mile, AI assistance (its Notebook Agent and Magic tools) to draft queries and analyses, and a publishing layer that turns notebooks into interactive apps and dashboards for non-technical stakeholders. It's built for analytics teams shipping answers to the business.
Clusy is experiment-first. The agent takes a goal — reproduce a paper, fine-tune a model, benchmark five approaches — plans the work, writes and runs the cells, and hands you a notebook you can branch to compare variants. Compute is part of the product: managed sandboxes from a free CPU tier up to H100 / H200 GPUs, which is the class of hardware model training actually needs.
The honest split: if your output is a dashboard or an app answering a business question, Hex is the stronger tool. If your output is a trained model, an evaluation table, or a research result, that's the work Clusy is built for.
Choose Clusy if…
- Your work is model training, fine-tuning, or research — you need GPUs, not dashboards.
- You want an agent that runs the full workflow, not an assistant that drafts cells.
- You compare many experiment variants and want branching built into the notebook.
- You're an individual or small team — a $0 start beats a per-seat platform.
Choose Hex if…
- Your team lives in a data warehouse and ships analyses to business stakeholders.
- You need polished, interactive data apps and dashboards as the deliverable.
- SQL is the primary language of your work, with Python second.
- You need mature enterprise collaboration: reviews, permissions, endorsed datasets.
Frequently asked questions
- Is Clusy a BI or analytics tool like Hex?
- No. Clusy can absolutely do exploratory analysis, but it doesn't publish dashboards or apps for stakeholders. Its job is ML and data science work — training, fine-tuning, evaluation, experimentation — done by an agent in a notebook you control.
- Can Clusy connect to my data warehouse?
- Yes — Clusy has direct Databricks and Snowflake connections, alongside file uploads and public sources like Hugging Face.
- Do Hex and Clusy overlap at all?
- At the edges. Both are cloud notebooks with AI in them. But Hex optimizes for analytics collaboration and publishing, while Clusy optimizes for agent-executed ML work on serious GPUs. Some teams use both: Hex for reporting, Clusy for modeling.
See the agent do the work.
Free plan, no credit card. Describe an ML task and watch it get planned, executed, and reported in a notebook you control.
Try Clusy free