If you can write a message to a coworker, you can run agnticr. Describe the job in plain words, or just describe how you work today and let Agnes work out what the job is. The team plans it, runs it, and accounts for every step.
agnticr puts your recurring work on autopilot.
Jobs run for hours, days or weeks.
They stop to ask you on WhatsApp or SMS when judgment is needed.
They get better every week.
You only ever talk to Agnes, your chief of staff
Tell her what you need, in plain language. A one-off instruction becomes a Todo she carries out; anything recurring becomes a Job. She briefs the right specialists, runs the work, and reports back. agnticr is a workforce that performs jobs for you, not a set of virtual colleagues you have to manage.
Routine work steals hours from what really matters.
Still on your list
Chase Anna for the delivery date
3 days ago
Find a time that works for all six
since Monday
Anything new in the tender inbox?
not checked today
Compile the monthly report
due Friday
Follow up the supplier certificates
since May
Until now, you had three options:
Do it manually
You and your team spend hours on work that doesn't need your judgment, only your time.
Verdict
Expensive, slow, soul-crushing.
Rigid workflow tools
Map every step into a flowchart, connect the APIsA doorway a system opens so other software can read and update its data — how the agents talk to your systems directly., maintain it forever.
Verdict
Works until reality deviates from the flowchart.
Paste it into a chatbot
Great for a one-off answer. But nothing happens unless you're there, prompting.
Verdict
Great answers — the work still waits for you.
Coding copilots and desktop AI agents made one person faster at their desk. But they're personal tools, and businesses don't buy tools for this kind of work.
They hire people.
agnticr is built to run the multi-step, multi-party, recurring workflows that drive a business, with AI that can be held to account for the result.
The fourth option: everything a good employee has, built into software.
Named specialists, each with their own craft, orchestrated by Agnes, your chief of staff. You talk to Agnes; Agnes runs the department.
Agnes
Chief of Staff
Understands your goal, delegates to the right specialist, and reports back. One chat, one phone number, one team.
Cindy
Research & verification
Kenth
Planning & ideation
Beth
Marketing coordination
Anders
Internal & external APIs
Anne
Connected services (Gmail, Dropbox …)
Davie
Structured business data
Joel
Email & outbound messaging
Jack
External correspondence, run to an outcome
Mike
Job creation & validated plans
Teddy
Documents, spreadsheets & reports
Philip
Project files
Wendy
Public web pages
Linda
Live voice
And the department grows. New specialists and Agent Services snap in without re-architecting anything.
03Getting started
“We don't know what to automate.”
Most automation asks you to already know what you want to automate. Start the other way round: describe something you already do, answer a few questions about it, and get back a proposal for how much of it can come off your plate.
What you write
Every month we chase unpaid invoices. Anna pulls the ledger, checks what has actually landed in the bank, emails everyone more than 30 days overdue, and tells me if anything is over €50,000 so I can call them myself.
What Agnes asks back
Which of those emails go out unchanged, and which does Anna rewrite?
What happens when a customer replies to say they have already paid?
Is the €50,000 threshold firm, or does it depend on the customer?
What comes back
Chase overdue invoices · monthly
Pull the ledger and match it against payments receivedAutomated
Draft one reminder per overdue customer, in your wordingAutomated
Send the remindersAsks you first
Log the replies, and stop chasing anyone who says they have paidAutomated
Call the customer yourself when it is over €50,000Stays manual
Before it can run
Your accounting system isn't connected yet. Named up front, so nothing fails halfway through the first run.
Suggested scheduleThe 1st of every month, 08:00
Nothing runs until you say so. What comes back is a draft job: read it, change it, or throw it away. And it will never pretend a step can be automated when it can't. From description to first live run is hours, not a pilot program — and that is the number we hold ourselves to.
04How it works
What setting one up actually looks like
No workflow builders. No decision trees. Describe the outcome; the team does the rest.
1
Describe the job — or just how you work today
“Every Monday, collect last week's signups, enrich them, send a personalized welcome, and give me a summary.” That's the whole setup. Don't have it phrased that neatly? Describe the process you run today and Agnes drafts the job for you.
2
Review a plan you can actually read
The planner turns it into a milestone plan with everything important stated up front: what it will do, and what it will never do without asking you first.
3
It runs — and keeps running
On a schedule, on a trigger, or on demand. Jobs survive restarts, wait days for replies, and never lose their place.
4
It asks before anything irreversible
Sending an email, changing a record, contacting a customer. Any of those and the job stops to ask you, on web, WhatsApp or voice. Answer from your phone; it adapts and continues.
5
It gets better every single run
Every run ends with a structured review. Useful learnings are kept and graded, stale ones retired, and the plan itself evolves, with a full audit trail.
05How it learns
Run ten beats run one.
Every product says its AI learns. Here is what that actually looks like: one job, tracked across ten runs, with a plan version you can point at and a diff you can read.
Chase overdue invoices · monthly
Run 1Plan v1
Your time12 minutes
Ran end to end, and stopped twice to ask which customers it should leave alone.
What it learned
Three customers are on a payment plan. They never get chased.
Run 4Plan v3
Your time4 minutes
Skipped the payment-plan customers without asking. You rewrote one reminder before it went out.
What it learned
Your second reminder is firmer than your first. Keep both, and use them in that order.
Run 10Plan v7
Your time40 seconds
One approval on WhatsApp. Two accounts flagged for a call before you thought to ask.
What it learned
The Malmö office always pays late and always pays. Flag it; don't chase it.
Every run ends the same way
1
Review
The run is examined against what it set out to do. Not summarized: examined.
2
Grade
Each candidate lesson is scored on whether it held up in practice, not on whether it sounded sensible.
3
Retire
Lessons that have gone stale are dropped, so last quarter's assumptions don't quietly pile up.
4
Reissue
What survives becomes a new numbered plan revision, with provenance for every change.
Whether a run succeeded is not the agents' own opinion. A separate judgment model delivers the binding pass-or-fail verdict against receipts they cannot fabricate: message ids, record ids, delivery confirmations, and the files they claim to have produced. A job can't talk its way to a pass or learn the wrong lesson from a run that only looked successful.
06How it feels
Monday, 07:00
A true-to-product scenario. Every step below is live in the product today.
07:00
The job wakes up
“Weekly member outreach” starts on schedule. Cindy gathers last week's signups; Davie cross-checks the records.
07:04
It reaches its gate
Sending email counts as irreversible, so the job stops and your phone buzzes on WhatsApp: “Ready to send 34 personalized welcomes — approve?”
Weekly member outreachApproval gate · WhatsApp
Ready to send 34 personalized welcomes — approve?
07:05 is your beat. One tap is the whole job.
07Use cases
What would you delegate first?
The kind of jobs businesses hand to agnticr:
Law firm
“Chase outstanding documents before every court date, and bring in a paralegal only when something is still missing.”
Clinic
“Recall patients due for follow-up, offer times, rebook the no-shows.”
Real estate
“Coordinate viewing times between sellers and prospective buyers, confirmed into everyone's calendar.”
E-commerce
“Watch supplier confirmations and chase delays before customers notice.”
Association
“Welcome new members, collect missing details, and send the monthly summary.”
Agency
“Compile the weekly client report from your project tools and send it for approval, every Friday at 07:00.”
Accounting firm
“Chase clients for missing receipts and documents before every VAT deadline.”
Restaurant
“Fill next week's shifts: ask the team, collect answers, confirm the schedule.”
Property manager
“Follow up fault reports with tenants and contractors until they're closed.”
08Capabilities
A desk, a phone, a filing cabinet and a database
Other platforms give agents a chat window. These are prebuilt tools that let them do the job instead of describing it, and each one has a specialist who works it.
Knowledge base
Load your documents, policies and know-how. Agents answer and act from your truth, not the internet's.
Cindy · works this one
Live voice
Linda takes and makes real phone calls. Approve a gate or brief the team by talking to it.
Linda · works this one
Native email & messaging
Email, WhatsApp and SMS are built in. Agents send, receive and follow up. No bolted-on integration.
Joel · works this one
Virtual file system
Every project has a real workspace where agents read, write and organize files, like a shared drive.
Agent-owned databases
Davie keeps structured business data that persists and grows between runs: registers, lists, records.
Davie · works this one
Connected services
Gmail, Dropbox and more. Governed connections, with credentials the AI never sees.
Anne · works this one
Your own APIs
Expose your internal systems as allowlisted operations. Anders works them safely.
Anders · works this one
Triggers & schedules
Jobs run on schedules, on events or on demand, and notify you on outcomes rather than noise.
Agent Services
Where the work actually happens
Generic AI gives agents a chat window. agnticr gives them purpose-built apps, each with its own data and a workspace you can watch, so they run the real multi-step, multi-party work your business depends on.
Other tools give agents a search box and a text editor.
agnticr gives them purpose-built apps to operate.
People Coordination
Agnes runs a real coordination process across a group: availability, choices, confirmations, all in its own workspace. The job waits for the outcome, for days if needed, then continues the moment it lands.
E.g. healthcare
A clinic fills Thursday's open shifts: the agent polls the staff group, collects availability and confirms the roster. The job continues the moment it's settled.
Workshop · 6 participants
Live
AAnna
Replied
EErik
Replied
SSara
Replied
JJohan
Replied
MMaria
Pending
OOmar
Pending
ProposedTue 14:00
4 of 6 confirmed. Nudging the rest, holding the slot.
External Agent Conversations
Jack runs goal-driven correspondence with people outside your company, all the way to completion, in a tracked thread you can watch the whole time.
E.g. construction
A builder needs three quotes. Jack runs the email threads with the suppliers to a decision, reminders and clarifications included, while you watch the progress.
Built with real businesses
Agent Services are built together with real businesses and made natively available to the agents. Each one is a general solution grown from a specific, real problem, and the catalog expands as new problems get solved.
Every job is a place, not a prompt
A durable workspace that runs, waits, builds up and improves over time. Not a box you type into.
Long-running & durable
A job can run for weeks and wait days mid-step for a reply or a coordination outcome, surviving restarts, never losing its place.
Built up over time
Each job keeps its own context, documents and materials. It accumulates what it needs instead of starting from scratch.
Learns from itself
Every run is reviewed: useful lessons are kept, stale ones retired, and the plan improves, with a full audit trail.
09The honest comparison
Copilots assist. agnticr delivers.
We love coding copilots and personal AI assistants; we use them daily. They're just built for a different job.
Coding copilots
Claude Code, Copilot
Desktop AI agents
Claude Cowork
Personal AI assistants
OpenClaw & friends
agnticr
Your AI workforce
Built for
Developers writing software
One knowledge worker's desktop
One person's life admin
Teams running a business
When you close the laptop
Pauses with your session
Scheduled tasks run remotely; the sandbox ends with the session
Some background tasks
Work continues server-side for days or weeks, and replays after a crash
Irreversible actions
You're right there to confirm
You confirm at the desktop
You trust your agents
Approval gates on your phone, and the job durably waits
Gets better over time
A fresh session each time
A fresh task each time
Remembers facts
Jobs review themselves; plans evolve with an audit trail
Your business systems
Local files & code
Local apps + personal connectors
Personal accounts
Governed connections; the AI never sees credentials
Users, projects & permissions
Personal
Org RBAC and SCIM; sessions aren't shared and projects stay local
Personal
Multi-tenant, role-based, project-scoped
Cost visibility
Flat subscription
Flat subscription
You manage it yourself
Per-run, itemized, on every job
Accountability
Chat history
Local files
Chat history
Every plan, decision, approval and result, persisted
AI models
One vendor's models
One vendor's models
Bring your own
A mix across vendors: frontier where judgment is needed, open-weight where volume is
Built for
One knowledge worker's desktop
Teams running a business
When you close the laptop
Scheduled tasks run remotely; the sandbox ends with the session
Work continues server-side for days or weeks, and replays after a crash
Irreversible actions
You confirm at the desktop
Approval gates on your phone, and the job durably waits
Gets better over time
A fresh task each time
Jobs review themselves; plans evolve with an audit trail
Your business systems
Local apps + personal connectors
Governed connections; the AI never sees credentials
Users, projects & permissions
Org RBAC and SCIM; sessions aren't shared and projects stay local
Multi-tenant, role-based, project-scoped
Cost visibility
Flat subscription
Per-run, itemized, on every job
Accountability
Local files
Every plan, decision, approval and result, persisted
AI models
One vendor's models
A mix across vendors: frontier where judgment is needed, open-weight where volume is
Copilots and desktop agents make individuals faster; agnticr makes organizations run. If your problem is “I need to get my own work done faster,” buy one of those. If your problem is “this work needs to happen every week without me”, that's us.
It does, and it's the closest cousin to what we do, so it deserves a straight answer. Cowork is a brilliant personal agent: it works your local files and apps, on your computer, for you. Four things change when the work belongs to a business instead of a person:
01
It's durability, not location
Cowork schedules genuinely run remotely now. What remains different is failure recovery: its cloud sandbox is destroyed when the session ends, and resuming after sleep can require a manual Continue. An agnticr job replays after a crash, survives reboots and deployments, and can wait three days for a customer's reply without losing its place.
02
Approval is a protocol, not a prompt
agnticr's gates are declared in the plan, enforced by the engine, and answerable from WhatsApp, web or voice by whoever owns the decision, and the approval becomes part of the quality record the job is judged against.
03
The tenth run must beat the first
Cowork's tasks start fresh each time. agnticr's jobs end every run with a structured review that grades what helped and what hurt, retires stale guidance, and evolves the plan itself, automatically, with an audit trail.
04
The work belongs to the company
Cowork has real enterprise controls: RBAC, SCIM, group spend limits, SIEM export and tenant isolation. The gap is ownership: sessions cannot be shared and projects are stored locally. An agnticr job is an organizational asset that colleagues can see, the right person can approve, and every run can be costed. Credentials stay server-side and agents reach only allowlisted operations.
Plenty of our users run Cowork or Claude Code for their personal work, and agnticr for the work their company depends on. That's exactly the right division of labor.
No — and the difference isn't that our flowchart is smarter. agnticr doesn't have one. Zapier, Make and n8n are excellent at deterministic flows you can draw in advance, node by node. agnticr is for work where judgment, conversation and approvals decide what happens next.
An agnticr plan is written from a conversation. It describes outcomes in two to eight milestones, not a tool-by-tool recipe, and it is rewritten when a run teaches the job something. A visual graph freezes when its author stops editing it; an agnticr plan is a contract that improves.
Workflow automation
Zapier, Make, n8n, Power Automate
agnticr
Outcome automation
You provide
A flowchart you design, node by node
A plain-language description of the job; the planner builds the plan
When reality deviates
The flow follows its design, and deviations need a new branch
Agents adapt mid-run: retry differently, escalate to stronger AI, propose plan changes with evidence
Judgment
The branches you design in advance
Real judgment at every step, plus an independent quality verdict on the outcome
Human in the loop
Real approval steps, wired into each workflow; several tools can wait days
Gates declared in the validated plan, answerable by live voice, and graded as part of the run's quality record
Maintenance
You maintain the flows as systems and needs change
Plans review and improve themselves after every run, with an audit trail
Communication
APIA doorway a system opens so other software can read and update its data — how the agents talk to your systems directly. calls and templated messages
Agents that converse: goal-driven email threads, group coordination, live voice
AI in the loop
Available as steps within the flow
AI-native end to end: planning, execution, review and learning
Who can own it
The person who builds and maintains the flow
Anyone who can describe the work
You provide
A flowchart you design, node by node
A plain-language description of the job; the planner builds the plan
When reality deviates
The flow follows its design, and deviations need a new branch
Agents adapt mid-run: retry differently, escalate to stronger AI, propose plan changes with evidence
Judgment
The branches you design in advance
Real judgment at every step, plus an independent quality verdict on the outcome
Human in the loop
Real approval steps, wired into each workflow; several tools can wait days
Gates declared in the validated plan, answerable by live voice, and graded as part of the run's quality record
Maintenance
You maintain the flows as systems and needs change
Plans review and improve themselves after every run, with an audit trail
Communication
APIA doorway a system opens so other software can read and update its data — how the agents talk to your systems directly. calls and templated messages
Agents that converse: goal-driven email threads, group coordination, live voice
AI in the loop
Available as steps within the flow
AI-native end to end: planning, execution, review and learning
Who can own it
The person who builds and maintains the flow
Anyone who can describe the work
The visual-workflow category is already moving: Flowise archived its repository, Relay.app shut down, OpenAI deprecated Agent Builder, and Salesforce moved away from its declarative agent-authoring path. That supports the direction, but it is not our proof on its own.
The honest exception is Microsoft's GitHub Copilot harness. It can own an outcome, choose its own steps and recover when one fails. What it still does not do is grade its runs and evolve its own executable definition.
When you should still use them: deterministic, high-volume data plumbing — sync rows, forward webhooks, copy form fills into a sheet. agnticr happily coexists: our agents can call your existing automations like any other system. The dividing line is simple: if the work needs judgment, conversation or approval, it's a job, not a flowchart.
And the AI agent builders? (Lindy, Relevance AI, Copilot Studio, CrewAI …)
They give you a workbench to construct your own agents: you write the prompts, design the orchestration, wire the guardrails, and keep it all working as models change. That's a great product, for teams whose business is building agents.
agnticr ships the finished department: a planner, named specialists, approval gates, self-improving plans, per-run cost tracking and tenant-grade governance, pre-built, integrated, and getting better on its own. You describe the work; you don't engineer the workforce.
10The platform
The unglamorous parts
Agentic work matters when it fits the way people already work. Human milestones connect agent execution to your process; access, cost, roles and models stay governed around it.
Agent work, connected to human work
Plans put human milestones beside agent milestones, each with an owner, deadline and proof of completion. One job coordinates what agents do, what people do and the handoffs between them — fitting agnticr into your process, not around it.
Your Systems. Your Rules.
Connect Gmail, Dropbox and your own internal APIsA doorway a system opens so other software can read and update its data — how the agents talk to your systems directly., and every agent works inside your context. Credentials are held server-side and never visible to the AI. Agents can only call the operations you've allowlisted.
A Paper Trail, Not a Black Box
Every plan, decision, approval and result is recorded, and every run comes with an itemized cost panel. You always know exactly what the AI did and what it cost.
Built for a Whole Business
Multi-user, role-based and project-scoped: give the right people the right access, run separate projects, and keep every tenant's data isolated. Governance that holds up as you grow.
Always Betting on the Winner
agnticr is model-agnostic by design, and deliberately runs on a mix. Frontier models from different vendors take the judgment calls; open-weight models take the high-volume mechanical steps. Every step goes to whichever model does that job best for the least money, and we re-tune that routing as the market moves. You never pick a model, learn a model name or migrate anything.
Nothing hidden
EU AI Act · GDPRThe EU's data-protection law — rules for how personal data must be stored, used and deleted.
Everything is on the record.
Everything the agents do is logged, auditable and available to you: how they reasoned, what they did, and what it cost, for every task and every job ever performed. No hidden steps, nothing you can't inspect, and human oversight built into the execution itself. Designed to meet the transparency and oversight demands of the EU AI Act. GDPRThe EU's data-protection law — rules for how personal data must be stored, used and deleted. is table stakes: your business data, customer registers included, is stored at rest within the EU, isolated per tenant, and visible only to the people you've authorized. The AI models that do the thinking may run outside the EU — but your business data is never used to train them, and never appears in anyone else's answers.
The three questions everyone asks
“Where does my data go?”
Stored in the EU, isolated per customer. Your business data is not used to train the models and cannot surface in anyone else's answers. Credentials are held server-side; the AI never sees them.
EU AI Act · GDPRThe EU's data-protection law — rules for how personal data must be stored, used and deleted.
“What if it gets something wrong?”
Anything irreversible stops and asks you first. And whether a run succeeded is settled against receipts the agents cannot fabricate — message ids, delivery confirmations — with every step on the record.
Approval gates · full audit trail
“Will it replace my people?”
It takes the chasing, the compiling and the coordinating — the hours nobody was hired for. Your people keep the judgment calls, and get those hours back for customers.
Connect agnticr to ChatGPT, Claude, Copilot, or any assistant that speaks MCPA standard plug (Model Context Protocol) that lets AI tools connect to other software — the same connector everywhere, instead of one custom integration per system. or Apps. Create jobs, approve work, and check what everything cost without leaving the tools your team already lives in.
ChatGPT
Apps & MCPA standard plug (Model Context Protocol) that lets AI tools connect to other software — the same connector everywhere, instead of one custom integration per system.
Claude
MCPA standard plug (Model Context Protocol) that lets AI tools connect to other software — the same connector everywhere, instead of one custom integration per system.
Copilot
MCPA standard plug (Model Context Protocol) that lets AI tools connect to other software — the same connector everywhere, instead of one custom integration per system.
Any MCP client
Open protocol
A
Your agnticr team
Agnes routes every request to the right specialist agent.
MCPChatGPT AppsA2A
Open standards, no lock-in. agnticr connects into your stack. Your stack doesn't have to move to us.
Plays well with others
A2A protocol
Already running OpenClaw — or your own agent?
Extend the agnticr team with your own custom agents over the A2A protocol. Your agents join the department; they don't compete with it.
11Pricing
You give the team a monthly budget
No seats, no tiers, no surprises. €10 or €200, you decide, and you follow exactly what every job run cost. You weigh cost against value continuously, with an itemized receipt for every run.
A budget you control
Set it per month, change it anytime. The team plans its work within what you've allowed.
Every run itemized
Each job run shows its own cost, like a taxi receipt. You always know what you got for the money.
No lock-in
Pause or stop whenever you like. Your jobs, plans and records remain yours, fully documented.
A worked example
Take a typical weekly job (chasing replies, compiling a report, following up signups) that takes about four hours a week today:
An employee does it
≈ €500/month
Around 4 hours a week of routine work, hours that could go to customers and core business instead
An agency or consultant does it
≈ €700/month
Skilled help, with onboarding, coordination and lead times on top
An agnticr job does it
Within your budget — e.g. €50/month
Runs every week, asks you when judgment is needed, and shows what every run cost
An illustrative example; your numbers will vary. The point is that hours move from routine work back to your core business and customer relationships, and that you can always weigh what a job costs against what it delivers.
Private beta
We’re onboarding the first businesses
Private beta is running right now, from one-person consultancies to 50-person firms, in any sector. Onboarding is a call, not a project — the first job typically runs within hours of it. Open beta follows in Q4. Get on the list to claim a spot before it does.
Q3 2026
Private Beta
First businesses are onboarding
Q4 2026
Open Beta
Doors open for everyone
2027
Full launch
Fully launched and ready
Accountable by design.
A whole department for the price of a tool: research, data, email, voice, coordination and integrations, staffed on day one. Reach it where you are, on web, WhatsApp, email or live voice. Your approvers never need to log in to keep work moving.
And the value compounds. The job that runs today is measurably better than the one that ran last month. Triggers instead of babysitting. Outcomes instead of noise. Jobs that grow the way good employees do.
Stop buying AI tools. Start extending your organization with agentic resources.
A team of specialist AI agents that plans, executes and improves your recurring business work, with human approval gates on WhatsApp, web and voice, and a full record of everything done and what it cost.
Delegate the work. Keep the decisions.Work that runs itself — and gets better every week.The first AI team with a memory, a plan, and a paper trail.
Tell us the first job you'd delegate and we'll put you at the front of the queue.
What happens next?
1We'll reach out as soon as a private-beta spot opens up for you
2A short onboarding call — you describe the first job you'd like to delegate
3Your team drafts the plan; you review it, approve it, and it runs
