SwarmMarshal · free desktop app for Windows & Mac

Give it your email. Get answers.

SwarmMarshal is a full mail and chat client — Gmail, Outlook, iMessage, Slack, Telegram, Discord — with an assistant that answers questions from your real messages. “What did the contractor quote me last fall?” gets the answer and the original email. All of it on your machine.

Windows & Apple Silicon Mac Local-first Source-cited answers You pick the model Keep your current mail client
SwarmMarshal assistant answering a question with cited sources
What it does

Everything your messages know, put to work.

Email and chat go in. Answers, timelines, briefings, and a clean inbox come out.

How it works

The magic ingredient is context.

A chatbot starts every conversation knowing nothing about you. SwarmMarshal does the opposite: it turns your own messages into durable knowledge, keeps it on your machine, and hands the right slice to the AI at the right moment.

Step 1

Your messages sync in

Email over IMAP and OAuth, plus iMessage, Slack, Telegram, and Discord — into a local database on your computer. Nothing is uploaded anywhere.

Step 2

Knowledge gets extracted

As messages arrive, a background pipeline pulls out the durable stuff: people, companies, commitments, deadlines, decisions. Every fact keeps a link to the message it came from — nothing is asserted without a source.

Step 3

A question assembles a context pack

When you ask, hybrid keyword + semantic search selects the relevant messages and facts — not your whole life, just the slice that question needs.

Step 4

The model answers from the pack

Whichever AI you chose — local or cloud — answers only from that grounded context and cites its sources. If the record doesn't contain the answer, it says so instead of guessing.

Why this beats a chatbot

You never re-explain who Acme is or dig up the thread yourself. The context compounds on your machine the longer you use it — and every answer can be audited by clicking through to the original message.

Models are swappable. Context isn't.

Because the knowledge lives with you, not the vendor, you can point it at a new model the day it ships — local or cloud — and it answers like it has known you for years.

Real screens · demo profile

This is the actual app.

Captured from a real profile, not a concept deck.

The knowledge it builds

The knowledge it builds

People, promises, decisions, and relationships extracted from your own history — each fact linked back to the message it came from.

Search by meaning

Search by meaning

Semantic and keyword search across every channel — find the message even when you don't remember the exact words.

A real, fast inbox

A real, fast inbox

Email, iMessage, Slack, Telegram, and Discord in one clean client. Everything it touches becomes searchable history.

Your day, briefed

Your day, briefed

The Today dashboard: what changed, who's waiting, deadlines, and what needs attention — with sources behind every fact.

Calendar & commitments

Calendar & commitments

Google and Microsoft calendars, plus deadlines and promises pulled from email — still linked to the original message.

You pick the models

You pick the models

Local models via Ollama or LM Studio next to cloud keys. Per-task routing, budgets, and a fully local option.

Full gallery →
Your data, your rules

Private by default. Powerful when you ask.

Your mail — and the knowledge built from it — stays on your machine. Each task goes to the right AI: a free local model for the routine and the private, a bigger model only when you say so.

Run fully local if you want

Every AI job in the app — sorting, extraction, search, even the assistant — can run on a free local model through Ollama or LM Studio. No cloud key required, ever.

A privacy floor the router enforces

Every AI call carries a privacy class. Work pinned local-only can never fall back to a cloud model — if no local model is available, it stops and tells you rather than quietly sending data out. Subscription CLI routes like Claude Code don't count as local, and the router knows it.

Costs that can't run away

Monthly budgets, a hard spend guard, and a message pipeline that prefers $0 routes — paying per message for routine mail processing is off unless you explicitly turn it on.

For the technical reader

The parts reviewers usually ask about.

It gets more interesting under the hood.

Models are benchmarked on your hardware

Model Scout runs calibration suites — built from the app's real production prompts — against the models your machine can actually hold. Routing preferences are gated on those scores, fail-closed: an unproven model doesn't silently take over your mail pipeline.

Local benchmarks →

It's an MCP server too

Point Claude Code, Codex, or any MCP-capable agent at your communication history. Your agent gets the same source-grounded search and context packs the built-in assistant uses — behind an explicit approval gate.

The MCP surface →

The architecture is documented

Message pipeline, knowledge graph, context engine, routing, and the trust model — written up properly for people who want to verify the claims rather than take our word.

Technical white paper → Architecture overview →
Try it properly

Kick the tires in ten minutes.

The fastest honest test of whether this is real:

Minutes 0–3

Install and connect one inbox

Gmail, Microsoft, or IMAP — the OAuth walkthrough takes a few minutes, and the first sync starts immediately.

Minutes 3–8

Ask something only your mail knows

“What did the plumber quote me?” “When does my lease renew?” Then do the thing no chatbot lets you do: click the citation and read the original message behind the answer.

Minutes 8–10

Switch the model out from under it

Flip the assistant to a local model via Ollama and ask again. Same context, same citations, zero cloud. That swap is the whole thesis in one click.

Part of the Swarm family

Better with the rest of Swarm.

Free to try

Install it, connect your accounts, ask your first question.

Every answer links back to the real message. Your data stays on your machine.