Talavine
Bring in the details
Connect supported accounts and add the notes and documents the job needs.
Agents
Help with the work you keep doing.
An AI agent is a helper you give a job. It can gather information, prepare a client update, or draft a follow-up using the accounts and files you allow. Set it up once for recurring work, then check its progress and review the results.
Drafts replies
Finds next steps
Your approval settings
Uses your information
Give a helper the job
Ask it to prepare a client briefing, find an unanswered question, or draft a follow-up.
They prepare work
Summaries, drafts, tasks, searches, and suggested rules are created.
You decide
Set when the helper needs your approval. Check important details and review what it prepares.
What it can do for me
Useful jobs an agent can take off your plate.
Each agent has a role, like a careful assistant who knows the difference between preparing work and making decisions for you.
Morning sorter
Shows you what actually needs attention before the day starts running you.
How it helps: It checks messages for urgent requests, dates, and people who need a reply.
Reply drafter
Writes the boring first version so you can edit instead of starting from a blank box.
How it helps: Draft-only mode means the agent can prepare text, but sending waits for your approval.
Follow-up keeper
Turns loose promises into reminders, tasks, and calendar-aware next steps.
How it helps: It finds dates, people, and next steps in your messages. Check the details before relying on them.
Junk reviewer
Keeps newsletters and repeat clutter from crowding out the people you care about.
How it helps: Your corrections can guide how it handles similar messages next time.
Memory helper
Remembers who someone is, what was promised, and where the last conversation left off.
How it helps: It connects related people, companies, and messages so you can trace the details back to their source.
Tool runner
Looks things up in approved tools so replies are based on real information, not guesswork.
How it helps: You choose the connected services it can use and the actions it is allowed to take.
You can see who is working on what.
The team dashboard keeps agents visible: reports, prepared drafts, review queues, and where work is blocked. Sally's Northstar packet stays a draft until she decides otherwise.
Tool use is shown, not hidden.
When an agent needs a tool or approval, the request appears in the conversation so you can understand the action before saying yes. And after the fact, every consequential action has a receipt. Ask "why did you do that?" and the answer comes from evidence. How the decision ledger works →
Teach a helper once. Let it carry the lesson forward.
Sally hires the Case Investigator for a narrow Northstar job, then teaches it one rule in a normal message: keep the renewal and the security-blocked expansion separate. The agent keeps that instruction with its source links and work journal, so it can prepare the next packet without pretending it can make Sally's decisions.
Next step
See it on day one
Give a helper one real job, on one mailbox.
A helper has a name, a narrow role, the sources it's allowed to read, and a visible activity log. You set the job, review what it prepares, and decide what it may do on its own, which starts at "draft only, nothing sends."
The safety bits
A little technospeak, translated.
The magic is less magical when you can see the safety rails.
Decide which actions need your review before the helper proceeds.
A support agent and a household admin agent can have different permissions.
Good answers point back to the messages or tools they came from.
Choose supported AI options to suit the work, your budget, and your privacy needs.
Start with messages. Let agents prepare the work.
The inbox feeds the agents; the agents feed you a smaller set of drafts, reminders, summaries, and decisions.