Metispace application / Signal & local AI

MARi

The answer is already
in your documents.

MARi is a private knowledge assistant for Signal that runs document search, embeddings, and language-model processing locally on your device. Teams receive clear, source-backed answers from approved internal documents without sending that material to a cloud AI model.

See how MARi works ↓
Operations Team12 members

Today

L
Leila

@MARi how soon do I need to return?

9:41 AM
M
MARi

Return within 10 calendar days after the notice is lifted.

9:41 AM ✓✓
Source: Evacuation Policy · section 4.2

Local chat, embedding, and vision models keep document indexing and AI processing on the MARi device, with tools to manage sources, test responses, monitor activity, and review answers.

Ask once. MARi does the finding.

No new portal. No new workflow. Your team asks in Signal and MARi returns a grounded answer with its source.

01

Mention @MARi

Ask a question in an approved Signal group.

02

Find the right source

MARi searches the active local document collection and selects the most relevant passages.

03

Answer with evidence

A local AI model writes a clear reply and MARi posts it back with source references.

  1. Signal group

  2. Local document index

  3. Local AI

  4. Source-backed reply

TM@MARi what does the policy say about refunds?

MRefund requests must be submitted within 30 days.Source: Refund Policy · section 2.1

Knowledge that stays useful.

From policy PDFs to photographed field guides, MARi turns the material your team already trusts into answers they can use.

01

Works where teams already talk

Mention @MARi in an approved Signal group. No separate app or new account for your team.

02

Grounded in your sources

Every answer is built from the active document collection and returns with source references.

03

Understands real-world documents

Index PDFs, Word files, notes, images, and scans. Local vision processing can transcribe photographed pages.

04

Reviewable by humans

See the full reply, retrieved sources, response time, audit notes, and human feedback in the local admin view.

Collections keep different knowledge domains separate—operations, HR, travel, finance, or the work unique to you.

Recent replies

All collections⌄All sources⌄
QuestionSource matchAuditFeedback
What’s the per diem rate for rural travel?Travel Policy.pdf
p. 14
2.4s✓ Correct
Do we require a safety brief before field work?Field Guide.docx
p. 8
3.1s× Wrong source
How should incident reports be submitted?Reporting Policy.pdf
p. 5
2.7s○ Needs review

Private by design.
Clear about the boundary.

MARi combines Signal’s end-to-end encrypted messaging with local document search and local AI processing.

01

Protected in Signal

Signal conversations are always end-to-end encrypted between participants. MARi joins as a group participant, so it can read and answer messages in groups where it has been added.

02

Processed locally

MARi uses local Ollama language, embedding, and vision models. Documents, vector indexes, retrieved context, OCR transcripts, model calls, and review logs remain on the MARi device; no cloud AI model is required.

03

Controlled by your team

Approved group access, device security, document permissions, and human review remain part of the operating model.

Encryption protects messages in transit. The security of the MARi device and who belongs to each Signal group still matters.

Signal is a third-party service. MARi is not affiliated with or endorsed by Signal.

MARi provides source-backed assistance from the document collection configured by its operator. It does not replace human judgment, policy ownership, access control, or review of high-impact decisions.

Read the MARi privacy policy