AIVM Brain vs Dust
A platform to build custom AI assistants, vs the governance-and-proof layer underneath any of them.
Dust is a platform for building and shipping custom AI assistants and agents over your connected company data. AIVM Brain is the governance-and-proof layer any model or agent reads through: per-person ACL-filtered retrieval, a content-blind tamper-evident audit you can verify offline, bring-your-own-model, and an optional on-chain anchor. They solve different halves of the same problem. Dust helps you build an assistant; Brain makes any assistant governed and provable. Many teams want both.
At a glance
| AIVM Brain | Dust | |
|---|---|---|
| What it is | A governance-and-proof layer any model or agent reads through | A platform to build and deploy custom AI assistants over connected data |
| Per-person access | ACL pre-filter: each person's query only ever reaches the sources they are cleared for, before retrieval, with field-level redaction | Spaces-based access control with SCIM-synced groups; an agent inherits the permissions of every Space it uses |
| Audit and proof | Content-blind audit you re-verify offline yourself, without trusting the vendor, plus an optional on-chain anchor of what the model answered over | Enterprise audit logs: tamper-evident, human-vs-agent attributed, streamed to your SIEM |
| Model and data | Bring your own model key; nothing you connect trains a model | Runs on Dust's platform; choose OpenAI or Claude; SOC 2 Type II and HIPAA, EU or US hosting |
| Getting started | One command: npx @aivm/brain init, on any stack | A Dust workspace; build assistants in its studio |
Why teams compare them
Dust is a strong, well-designed product for assembling assistants quickly. Teams comparing it to Brain are usually weighing a build-and-deploy studio against a governance layer they can prove to an auditor. The right answer depends on whether you mainly need to build assistants, or to govern and prove what any assistant is allowed to see.
Build an assistant, or govern and prove one
Dust is at its best when you are assembling and shipping assistants: connect your tools, compose an app or agent, and put it in front of your team. Brain is not an assistant builder; it is the layer underneath that decides, and proves, what any assistant is allowed to see. If your goal is to build assistants fast, Dust is excellent. If your goal is that every assistant only ever answers from what each person is cleared to see, and you can prove it, that is Brain. The two compose: build in Dust, govern through Brain.
Both have access control and audit, so what is different
Dust has real governance: Spaces-based permissions, SCIM groups, and Enterprise audit logs that are tamper-evident and stream to your SIEM, plus SOC 2 Type II and HIPAA. That is strong. The difference is two things. First, what the audit can PROVE: Dust's logs are tamper-evident and SIEM-streamed; Brain's are content-blind and INDEPENDENTLY verifiable offline, so your auditor re-checks the whole chain themselves without trusting the vendor, optionally anchored on-chain. Second, the job: Dust governs the assistants you build in it; Brain is the layer underneath ANY assistant or model, filtering every retrieval to the asker's cleared sources first, with your own model key.
Where Dust is the better fit
If your priority is a polished studio for building and deploying custom assistants and agentic workflows over connected data, Dust is a genuinely strong product and a faster path to a working assistant. Brain is the better fit when you want provable governance, per-person access, and model and data ownership beneath whatever you build.
Who each is best for
Questions, answered
Is AIVM Brain a Dust alternative?
They overlap but solve different halves. Dust is a platform for building assistants over your data; Brain is the governance-and-proof layer any assistant reads through, with per-person access and a verifiable audit. Many teams build in one and govern through the other.
What can Brain prove that an assistant platform does not?
Brain filters every retrieval to what the asker is cleared to see before the model runs, and records each access in a content-blind, tamper-evident log an auditor can verify offline, optionally anchored on-chain. That is provable governance independent of which assistant or model is in front of it.
Can I use both?
Yes. Build assistants where you like and point them at Brain's governed tools so every answer is access-filtered and recorded, with your own model key.