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OneSchema Studio

The AI Cowork for big data.

Connect any data source, analyze and automate with AI, and turn what works into something your whole team can reuse — even on big data.

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IT approved

Scalable and compliant at enterprise scale

Not just a personal scratchpad. Designed from the ground up for regulated industries, with access control, self-hosting, and governance.
Granular access control for collaboration
The power of collaborative AI even on your most sensitive and business critical data.
Big data ready, with our lakehouse engine
Our interactive data grid feels just like Excel on multi-million row datasets. Blend the power of AI agents with the familiarity of a spreadsheet.
Secure in your own cloud
AWS, Azure, and GCP are all natively supported for self-hosting. SOC 2, HIPAA compliant.
The ONeSchema Difference

OneSchema Studio vs. Claude Cowork

Both put an AI agent in front of your data, and both are good at what they were built for. The difference is what surrounds the agent: Claude Cowork is a coding agent that lives in a repository, while Studio is a data-operations workspace wired into your pipeline from day one
Where it runs, and what persists
A collaborative cloud workspace your team opens in a browser — nothing to install. Sessions are saved and carry memory of the work, so a teammate can reopen a project and pick up in full context instead of starting over. Nothing is trapped on one laptop.
A local CLI in your terminal or IDE. Source files stay on the machine and only relevant snippets go to the cloud for inference — so neither fully cloud nor fully offline. Sessions and memory files do persist, but on the individual machine that ran them, and every user installs and maintains their own setup
Getting data in and out
Managed connectors for S3, GCS, Azure Blob, SFTP, and enterprise systems like Salesforce and Workday — pull source files in and deliver results back out.
Can reach external systems through MCP servers or scripts a user writes, but there are no managed, built-in data connectors to configure
Working with large, tabular files
An editable data grid built for large tabular files — see the data, correct it in place, with autosave and real-time feedback
Terminal- and IDE-based. No visual spreadsheet or grid, so inspecting a wide, messy file means reading it through text output
Schema and validation governance
OneSchema Templates enforce your organization's schema rules and validations on every file, consistently across the team
No built-in schema or template governance. Validation rules are whatever each user writes into their own code
Shared, reusable team knowledge
A centrally governed library of Templates and Skills, curated for the organization and available in every session by default.
Skills and plugins do exist and can be shared through version control or installed as plugins — but they are ad hoc markdown and config files, not a governed library.
Recurring production runs
Promote a proven session into a Workflow — a version-controlled pipeline that runs on a schedule or via API.
No built-in recurring, Workflow-style delivery. Scheduling and reruns are something you assemble yourself.
Connectors

Connect to what you already use

Plug into our curated library of pre-built connectors. If your go-to app is missing, just ask—we’ll build and ship it for you in under 5 days.
USE your own AI

Use the best model for every job with no lock-in

Connect any models that have already been approved. Full visibility and control for both governance and spend optimization.
Intelligent model routing
Get more output with every dollar spent. Route complex tasks to more expensive, thinking models and simple tasks to smaller models.
Bring your own key
Connect your LLM provider with the security and retention agreements, negotiated rates, and security posture, IT has approved.
Open and closed models. No Lock-in
Run on major closed-source models, or on open-weight models hosted on your own infrastructure. Either way, you're never boxed into a single vendor's pricing, roadmap, or performance ceiling.
Model gateway
Centralize observability and governance across all of your models. All of your usage and spend controls in one place.
Use cases

What a session in Studio actually looks like

A few real shapes of work teams bring to Studio — each one a file (or a few) that needed to go from messy to usable.
Merge two CRMs into one clean schema
  • Combine Salesforce account exports with a HubSpot company file, match by domain, flag duplicates, and load one standardized account list — reviewed in the grid before it ships.
Load a new enterprise customer's data
  • Take a customer's roster or catalog, map it to your schema, validate required fields, and get them live — without opening an engineering ticket.
Turn a PDF or multi-tab Excel into a usable file
  • Pull tables out of scanned statements, invoices, or multi-worksheet exports into a clean CSV, ready for the next step in your process.
Save what worked as a Skill
  • Turn a proven cleanup or mapping pattern into a reusable Skill your teammates can pull from — so it isn't rebuilt from scratch next time.