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Sandstone vs ChatGPT: A General-Purpose Assistant, or a System for Legal Work?
Most legal teams already have ChatGPT, and it's useful for drafting, summarizing, and thinking through a problem. Sandstone does something different: it captures the request that arrived in Slack, carries what you agreed with that counterparty last year, enforces who can see what across your systems, and records how long the work took. Here's a side-by-side.
Sandstone vs ChatGPT
| Capability | Sandstone |  ChatGPT |
|---|---|---|
| Primary focus | AI-native operating system for in-house legal work | General-purpose AI assistant |
| Where work starts | Requests captured from Slack, email, and business systems as they arrive | A person opens a chat and describes the task |
| Business context | Counterparty history, prior decisions, and relationships mapped into a knowledge base that compounds | Whatever is pasted in, plus connected files where configured |
| Playbooks | Built from your existing contracts and precedent, applied consistently across every request | Applied through prompts and custom instructions |
| Permissions across systems | Permissions mapped across every connected integration | Workspace-level controls |
| Record of the work | Every request tracked from arrival to resolution | Chat history |
| Data handling | Enterprise controls with zero-data-retention commitments | Business and Enterprise tiers do not train on conversations; consumer tiers do by default |
| Best fit for | Teams that need legal work captured, executed, and measured | Individual drafting, summarizing, and thinking through a problem |
Based on publicly available information as of September 2026. Names and trademarks belong to their respective owners. If anything here is inaccurate or out of date, contact us and we'll update it.
Frequently asked questions
Keep using it — Sandstone isn't trying to replace the thinking tool. Sandstone handles what happens around it: the request captured on arrival, routed to the right person with history attached, worked through defined steps, and recorded so you can report on volume, ownership, consistency, and cycle time. Those are system questions rather than prompt questions.
Partly, but a custom GPT only applies your playbook when someone opens it and asks. What's harder is everything that isn't the model: capturing requests from the channels the business actually uses, enforcing permissions consistently across systems, requiring an approval before something goes to a counterparty, and producing a defensible record. That's the part Sandstone is.
Sandstone selects across frontier models by task, so the model layer is genuinely shared. The product is the layer around it — the context, the permissions, the workflows, the record. We'd rather be straightforward about that than pretend otherwise.
Sandstone runs with enterprise access controls and zero-data-retention commitments. Our Trust Center (trust.sandstone.com) has the details, and we've written about privilege and confidentiality when using AI. If your team is currently pasting contract text into a consumer tier, that's worth checking against your own policy today, whatever you decide about us.
