WorkerKit

Enterprise AI workers

Turn your AI tools and apps into an AI workforce.

AI workers that carry out the job, retain its method and history, and can improve over time. Your company controls what they can access and spend.

Why WorkerKit

AI supplies the intelligence. Your company keeps the authority.

Connecting your apps to AI only pays if you can let it act. These four are what let a company connect everything without handing everything over.

  • One source of truth for how work gets done. How a job is done lives in one reusable kit: instructions, apps, permissions, schedule, budget and model. Every worker installed from it runs it the same way, and when the kit improves, those workers can take the update.
  • Authorize the job. A worker reaches only the apps, actions and fields you allow, never everything the person who asked could reach. App logins never pass through the AI, and a call outside what you granted is refused and recorded.
  • Set the limits. Keep the record. Spending stops at the limits you set per run, per day and for the whole account, even with several jobs running at once. Every run leaves a record of what it read, what it changed, what it was refused and what it cost, kept in your account.
  • Workers that learn as they work. Results are held to your quality criteria, so weak ones get caught early. A better way of doing the job is proven on real runs before it takes over, with your approval or within your limits. What a worker learns stays with your company.

Your workforce in action

One worker is a start. A workforce keeps work moving.

Workers run in the background, on schedules or when events arrive. They watch your connected apps, hand work to each other, and bring important information to the right person in time to decide. Your team doesn’t have to ask for every update.

  • Sweep ten inboxes, Slack and Intercom twice a day, then escalate what cannot wait Escalation orchestrator: Starts the sweep at 07:30 and 19:30, calls the three scanners at once and, when any of them reports a critical case, calls the worker that checks the account and the runbooks. Nothing waits on a person. Scan 10 support inboxes: One decision worker over all ten support inboxes: it reads every thread that arrived since the last sweep and sorts each one as critical, normal or noise, by the rules the kit sets. Nobody can log in, an outage, data loss or a failed payment is critical. Scan #support: Reads the new messages in #support since the last sweep and sorts each thread the same way, so a customer who wrote in Slack is caught as surely as one who emailed. Scan the Intercom inbox: Reads the open Intercom conversations through the company’s own Intercom MCP server and sorts each one as critical, normal or noise. Check the account and runbooks: For each critical case, finds the account in HubSpot, reads the runbooks in Confluence for the symptom and returns the account, its plan and the fix to apply. Post, tell the reps, reply: An Action worker with no model: it posts the escalation to #support-escalations, messages the account’s reps and sends the customer the first reply, exactly as it was handed them. Six workers, two models, and nothing waits on a person.
  • Sweep Search Console, the rankings and the site every Monday, then fix what slipped SEO orchestrator: Starts the sweep every Monday at 06:00, calls the three pulls at once and hands what they bring back to the worker that finds what slipped. Pull Search Console: An Action worker with no model: it pulls the last 28 days of clicks and impressions by page from Search Console, exactly as asked. Check the rankings: An Action worker with no model: it reads the tracked keywords’ positions from SEO Tools and returns which slipped and which rose. Crawl the site: An Action worker with no model: it crawls the site with Firecrawl and returns broken links, slow pages and missing titles. Find what slipped: Puts the three pulls together with Google Analytics, finds the pages whose clicks fell 30 percent or more and names the likely cause of each. Draft the fixes: Writes the fix for each page, a new title, the links to repair, one rewrite, as a draft in Drive for the team to edit. Open the tasks, update the tracker: An Action worker with no model: it opens one Linear task per fix, links the draft and updates the tracker sheet, exactly as handed. Seven workers, two models, and nothing waits on a person.
  • Set a new employee up before day one Sort the request: Reads what arrives in the people@ inbox and sorts it: a new starter, a leaver, a change of role or something else, with the name, the team and the start date. Read the role’s access set: Looks the role up in the onboarding pages in Confluence and returns the accounts, channels and equipment that role gets. Find the team’s channels: Finds the Slack channels the team’s members share and returns the ones a new account executive in EMEA is added to. Check the equipment list: Checks the equipment sheet for a laptop and a monitor in stock and returns what can ship before day one. Find the onboarding guide: Finds the current onboarding guide for the role in Drive and returns its link and its two-week plan. Draft the setup plan: Writes the setup plan from the three findings, the accounts to create, the channels to join, the orientation to book and the buddy to ask, and puts the question to the IT lead. Invite, ticket, schedule, welcome: An Action worker with no model: it sends the Slack invites, opens the IT tickets, books the orientation and sends the welcome email, exactly as the plan says and only after Tyler’s yes. Seven workers, four models, one person’s yes.
  • Turn a competitor’s price cut into an approved response Watch competitor pages: Watch the competitor’s pricing page and flag a meaningful change for another worker to verify. Check the source: Reopen the source, check the promotion’s timing and keep unanswered questions visible for the workers that follow. Compare the offer: Compare the verified offer with your company’s plan so the team can see the size of the pricing gap. Find the deals at risk: Review CRM records and recent engagement to identify the accounts most exposed to the competitor’s offer. Find our best answer: Look through customer calls and company knowledge for a response grounded in the strengths buyers care about. Plan the response: Bring the three findings together, prioritize accounts and draft a response. Ask for a person’s approval before offering the discount. Send what Maya approved: Send the prepared response only after both the drafts and Maya’s approval arrive. The approved account list sets the scope of the send. Seven workers, four models, one person’s yes.
  • Qualify and answer every inbound lead Qualify the lead: Reads the new form submission in HubSpot and decides whether the lead fits: company size, region and the use case named, by the rules the kit sets. Research the account: Searches the web for the company: size, what it does, recent news and open roles, and returns a short profile. Check past conversations: Searches email and the CRM for earlier contact with the company or the person and returns what was discussed. Pick the owner: Picks the account executive who owns the lead from the territory rules: region, segment and current load. Find matching proof: Finds the case study or reference closest to the lead’s situation in Drive and returns it with one line on why it fits. Draft the first reply: Writes the first reply from the research, the history and the proof, proposes two meeting slots and puts the draft to the owner. Send and log it: An Action worker with no model: it sends the reply and creates the deal and the follow-up task in HubSpot, exactly as approved. Seven workers, four models, one person’s yes.
  • Chase overdue invoices, and only those Receivables orchestrator: Starts the sweep at 16:00, calls the three pulls at once, matches payments and promises against what is past due and calls the check for what is still owed. Pull the receivables sheet: An Action worker with no model: it reads the receivables sheet and returns every invoice past its due date. Pull payments received: An Action worker with no model: it reads the payments received since the last sweep from Stripe and returns them by invoice. Read the billing inbox: Reads the replies in the billing inbox and returns who promised to pay, who disputes an invoice and who asked a question. Check the contract terms: Finds each customer’s contract in Drive and returns the payment terms and the late fee that applies. Draft the reminders: Writes one reminder per invoice still owed, firm but friendly, with the terms that apply. Send and update the sheet: An Action worker with no model: it sends the reminders and marks each row in the receivables sheet, exactly as handed. Seven workers, three models, and nothing waits on a person.

A workforce for every team

Put AI workers on jobs with real ROI.

Each kit defines a worker’s job, apps and limits. Some kits work with other kits to set up a connected group of workers.

  • Sales Deal Follow-up Assistant, Inbound Lead Qualifier, Meeting Prep Assistant. Connected workers: Sales Handoff Workflow.
  • Customer success Renewal Radar, CRM Scribe, Meeting Prep Assistant. Connected workers: Customer Success Plan Workflow.
  • Marketing SEO Watchtower, Competitor Site Pulse, Lost Backlink Recovery. Connected workers: Campaign Learning Workflow.
  • Leadership & ops Executive Daily Briefing, Decision Queue, Weekly Ops Reporter. Connected workers: Company Operating Review Workflow.
  • Engineering Engineering Pulse, GitHub Issue Triage, Daily GitHub Repo Briefing. Connected workers: Release Readiness Workflow.
  • Finance Invoice Follow-up Assistant, Follow-Up Tracker, Close Reconciliation Evidence. Connected workers: Month-End Close Review Workflow.
  • Support Support Inbox Triager, Company Knowledge Concierge, Email Reply Needed Screen. Connected workers: Support Resolution Planning Workflow.
  • IT Internal Request Router, Access Register Evidence Review, IT Request Closure Review. Connected workers: Access Review Preparation Workflow.

Get started

Start with one job.

WorkerKit is in early access. Join the waitlist and we’ll email you when your invitation is ready.

  1. 01

    Request access.

    We’re inviting teams in stages.

  2. 02

    Connect your agent and apps.

    Once invited, add WorkerKit to the agent you use and connect the apps the job needs.

  3. 03

    Run your first worker.

    Choose a kit, review its access and limits, and run it on demand or on a schedule.

Bringing a bigger process?

Tell us the outcome and the apps involved. We’ll help you plan the workers and handoffs.

  • Talk to us Open the brief to discuss your process.

Questions

Before you connect everything.

  • My assistant already runs scheduled tasks. What is different? WorkerKit gives each job a persistent worker with its own permissions, budget, memory and run record. Authorized people and agents can use that worker, and schedules or events can start its work.
  • Is this only for recurring work? No. A worker runs on demand, when an event arrives, or on a schedule. Between runs it keeps its instructions, its access and its memory, so the next run starts ready.
  • What stays after a run ends? The worker: its instructions, its app access, its limits and its memory. And the record of the run, in your company's account: what it read, what it changed, what it was refused and what it cost.
  • Do my credentials or sensitive data reach the model? App logins never do: WorkerKit holds them and makes the calls. For the built-in apps you can also hide the fields you choose from the model, and a call outside what you granted is refused and recorded.
  • We already have engineers and AI tools. Why add WorkerKit? Keep your methods. WorkerKit supplies what every one of them would otherwise need built and kept alive: the app connections, the access controls, the spending limits, the schedules and the record. Your engineers write the job, not the plumbing.
  • How do we reduce checking and correction? Give each worker a focused job and clear quality criteria. Route uncertain decisions to a person, and prepare drafts where review matters. Language workers can test instruction changes against real runs before applying them, with your approval or within the limits you set.
  • Who maintains the app connections? WorkerKit maintains its built-in app connections. Connect an account once, then give each worker the access its job needs. If a login expires, reconnect that account. For custom MCP connections, you or the provider maintain the MCP server.
  • Will this be economical at volume? Each kit comes with a starting model, which you can change for the job. Decision workers can route only the work that needs a more expensive step. Use the editable kit estimates to include setup, review and running costs, then use run records to measure cost per acceptable result.
  • What can a worker change in our applications? Only what you granted: the apps, the actions and the fields. Anything else is refused and recorded. An allowed action is still an action, so stopping a run does not undo what it already did, which is why a job can draft instead of send.
  • Is this like AI coding agents? One step on from them. Coding agents do whole tasks because they can reach the whole repo and its tools. WorkerKit connects your apps and your company's knowledge the same way, so AI workers can do a job rather than help with it, from Claude, ChatGPT, Gemini, Copilot or any MCP client.
  • Can we start today? Browse kits and agent setup guides today. Accounts open by invitation through the waitlist in Get started. Once invited, connect your agent and apps and run your first worker. Bringing a bigger process? Open Talk to us beneath Get started. Plans and usage rates are on the pricing page.

Turn AI from a tool your people use into a workforce your company runs.

Connect the stack. Give AI jobs of their own. Keep the record.