Primary workflow
Email tasks, already done
When an email asks you to write something, Corivo understands the request, drafts the document from your work context, and replies to the thread.
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Feature
A local AI agent that already has your work context.
A local AI agent is not a separate tab you visit after compressing your day into a prompt. Corivo lives beside your work on Mac and Windows, sees the active context, reaches into the tools you have connected, and handles the task from there.
The problem
Why a local AI agent
Most AI tools live in a separate tab. You start each conversation with a blank text box, paste in the email or ticket, explain who the project is for, then ask the question. A local AI agent removes that handoff and lets short commands actually mean something.
Generic chatbots have zero context. Even with memory features, they only remember what you typed inside their chat product. They cannot see the document you have open or the ticket you are reading right now.
Browser tabs are not where work happens. Replies live inside your mail app. Tickets live inside Linear or Jira. Documents live in Notion, Google Docs, or local files. A local AI agent meets work where it actually is, across every app on your desktop.
Cloud-only agents trade privacy for capability. Sending an entire codebase or every email through a remote model is a hard sell for any team handling regulated data. A local agent keeps the data path on your machine and only sends the specific prompt that an inference call needs.
What it does
The useful parts, not another chat surface.
Starts with the work in front of you
The active ticket, email, document, or selected text becomes part of the command before you paste anything.
Pulls the missing background
Connected tools fill in the thread, issue, commit, calendar, or document history behind the immediate ask.
Acts from your computer
The local agent can read files, draft replies, inspect projects, and run the commands you authorize on Mac and Windows.
How it works
How the local agent works
Corivo combines active screen context, local capture history, and connected-tool retrieval before handing the task to its agent runtime on your computer.
- 01Screen context answers what you mean by this ticket, this doc, or this thread.
- 02Tool context supplies the project background that is not visible right now.
- 03The local runtime executes the work from your machine with the permissions you grant.
Corivo runs as a desktop application on Mac and Windows. The agent runtime, the local capture layer, and the connector cache all live on your computer rather than on a Corivo server.
Active context is captured through the operating system's accessibility APIs — macOS Accessibility on Mac and UI Automation on Windows. Both expose structured text from the focused window, not pixels, so the local AI agent reads the right thing without screenshots.
When a command needs background that is not currently visible — the full email thread, the parent ticket, the meeting notes — connected tools like Gmail, Notion, Linear, Slack, and GitHub supply that on demand. Retrieval happens in the moment, using your credentials.
Token rotation, API keys, and session credentials stay in the operating system keychain (macOS Keychain on Mac, Credential Manager on Windows). Capture history stays in a local SQLite database you can inspect, export, or delete.
Typical workflows
Where this shows up in real work.
Drafting a reply from a real thread
An email asks you to write a proposal. The local AI agent reads the active Gmail thread, pulls the project context from Notion, drafts the reply in your voice, and writes it back into the compose window. No copy-paste loop into a separate chat tab.
Closing a ticket without context-switching
While reading a Linear ticket, ask the agent to write the resolution note. It already has the issue body and the comment thread. It can also reach into the connected repository to mention the fix and the commit that landed it.
Recovering yesterday's decision
You agreed to something on a call but cannot remember the wording. The agent searches your local work memory, surfaces the meeting snippet, and reminds you what was actually said, with the surrounding context to quote.
Pre-meeting briefing
Open Calendar. The agent pulls upcoming meeting attendees, their recent threads, and the docs you exchanged, then assembles a one-page brief before you join. Brief lives next to the calendar event, ready to skim.
Answering email about a project you forgot
Someone replies on a six-week-old project. The agent retrieves what you decided, what you shipped, and what is pending, so the reply is grounded in real history instead of a vague apology.
Use cases on video
Watch the capability show up in real workflows.
Related workflow
Ask about selected text
Highlight a line in an article and ask a short question. Corivo answers through the lens of your own product and positioning.
Related workflow
Turn scattered data into a campaign plan
Corivo connects product updates, competitor movement, and revenue data, then turns those signals into a complete activity plan.
How it differs
How a local AI agent differs from a chatbot
Chatbots wait for you to brief them. A local AI agent already knows what you are looking at. That single shift removes most of the prompting overhead that makes generic AI feel like a chore.
Memory features inside one chatbot — ChatGPT Memory, Claude Projects — only remember what you typed in that chatbot. They cannot see your inbox, your calendar, or your local files. A local agent can, with your permission.
An agentic web app can call APIs, but it cannot reliably know which Linear ticket you are looking at, which Notion page you opened, or which paragraph you selected on your screen. A local AI agent can, because it runs on your computer with the operating system's accessibility APIs available to it.
ChatGPT / Claude
Chat surfaces with memory features inside one product. They cannot see your active app or local files. A local AI agent can, with your permission.
Cursor / Copilot
Coding agents inside one IDE. They know your repo but not your email, your tickets, or your calendar. Corivo's local agent works across every app on your desktop.
Cloud assistants (Glean, Microsoft Copilot)
Server-side enterprise agents that index your SaaS centrally. Corivo runs the agent itself on your machine and only retrieves from connected tools on demand.
FAQ
Common questions.
What is a local AI agent?
A local AI agent is software that runs on your computer, sees the work you are currently doing through operating system APIs, and executes commands using both that local context and the tools you have connected. The agent runtime lives on your machine rather than inside a remote chat product, so it can act on what is actually in front of you.
Does Corivo work on both Mac and Windows?
Yes. Corivo is built for Mac (Apple Silicon and Intel) and Windows. The same local AI agent, the same connectors, and the same Pro features are available on both platforms. The Mac build ships first on each release; Windows builds follow on the same release line.
Does the agent need an internet connection?
The agent talks to a model provider to generate responses, so internet is required for the inference call itself. Local context, capture history, and tool credentials all stay on your machine — only the prompt and the model response cross the network.
Can I bring my own model or API key?
Yes. Corivo supports your own model provider key, so you can route inference through OpenAI, Anthropic, or your team's preferred endpoint. The local agent runtime stays the same regardless of which model answers.
What can the local AI agent actually do on my desktop?
It can read the active window through accessibility APIs, search your local capture history, query connected tools (Gmail, Notion, Linear, Slack, GitHub, Calendar, and more), and execute commands like drafting replies, writing documents, or summarizing threads. You explicitly grant each capability.
Is the agent open source?
The desktop runtime is open source under Apache-2.0, so the local-first implementation is inspectable by anyone. The closed cloud portion handles billing, sync, and team features only — it is not in the path between your work data and the model.
How does Corivo handle data privacy?
Capture history stays in a local SQLite database on your computer. Connector credentials stay in the operating system keychain. Nothing about what you read, write, or remember is sent to Corivo servers. Only the specific prompt for an inference call crosses the network, and you can inspect it.
Related paths
Keep following the thread.
How Corivo works
The four-loop model behind the local agent.
Screen contextHow the agent reads the active window without screenshots.
Work memoryLocal searchable history of recent work surfaces.
Tool contextNotion, Slack, Linear, Gmail, GitHub on demand.
Privacy controlsWhat stays local, what gets sent, what you can erase.
Corivo vs ChatGPT memoryHow a local agent differs from memory inside one chat product.