What is a managed AI employee?

A role-specific AI system that performs one recurring business function inside your workflow, with ATI handling implementation, management, and ongoing improvement.

Is this just a chatbot?

No. The role is built around execution inside tools and workflows, not just conversation. It can read inputs, make bounded decisions, update systems, and escalate when needed.

What happens when it doesn't know the answer?

It hands the case to the person you choose, with the full conversation, and we add the missing answer to its knowledge.

How long until it's live?

It depends on the role and how many tools it connects to. We agree a go-live date with you when we scope the role, so you know the timeline before the build starts.

Do we need a large company for this to work?

No. Smaller teams often benefit faster because one managed AI employee can remove a meaningful amount of repetitive operational work.

Can ATI manage it after launch?

Yes. That is part of the model. We do not just deliver a build and disappear. ATI manages performance, improvements, and workflow reliability over time.

AI employees for sales, support and admin

The leads and tickets that wait overnight get answered in minutes

We set up an AI employee for one repetitive job: answering support tickets, qualifying leads, or moving data between your tools. It works in your inbox, CRM and helpdesk 24/7, hands anything unusual to your team, and we monitor and tune it every month. $2,000 once, then $500/mo.

Scope my AI employee How it compares to a hire Pricing

24/7
Replies at 2am, on Sundays and during launch spikes: $2,000
One-time setup to build the employee: $500/mo
Ongoing management and improvement

Example role

ATI AI support rep

24/7 active

Reads: Tickets, chats, docs, account context, knowledge base
Does: Answers, routes, escalates, updates systems, reports status
Managed by ATI: Monitoring, tuning, issue review, workflow improvements

Example activity

Illustrative

02:14Answered "Where is my order?" (resolved)
02:31Refund above limit → escalated to your team (escalated)
06:05Logged a new FAQ gap for review (resolved)
07:58Updated CRM records from overnight tickets (resolved)

Outcome

Customers get an answer while your team is offline.
Your team only sees the tickets that need a person.
We review its answers monthly and fix what it got wrong.

Why this exists

Most teams do not need more software. They need another worker.

We build one AI worker for one job, connect it to your tools, and stay responsible for how it performs.

Hiring takes months, and the backlog doesn't wait.

Recruiting, onboarding and training a new rep takes weeks before they clear a single ticket.

A chatbot answers questions. It doesn't do the work.

It can't update your CRM, route a ticket or chase a follow-up, and nobody fixes it when it is wrong.

Your best people are stuck on copy-paste work.

Hours a week go to the same replies, the same data entry, the same status updates.

The numbers

How a managed role compares to a traditional hire

This is not a claim that AI replaces every person. It is a better operating model for narrow, repetitive, process-driven work. Use it for work where the same request arrives dozens of times a week. The only variable cost is AI usage, which we estimate before you sign.

Annual cost

Human employee$30,000 - $90,000

ATI AI employee$6,000/yr + AI usage

AI employee cost = $500/mo management, 12 months, plus AI usage estimated up front.

Hours covered per week

Human employee40 of 168

ATI AI employee168 of 168

The 40 hours are before PTO, sick days and meetings.

Dimension	Human employee	ATI AI employee
2 AM coverage	Not available	Already working
Ramp-up	2-4 weeks of onboarding	ATI builds and deploys the role
Consistency	Varies by person and workload	Same rules and answers every time
Sick days	Yes	No
Needs managing	Internal manager time	Minimal, and ATI handles most of it
Scale to 2x volume	Hire another person	No additional headcount
Ownership	They quit, tribal knowledge leaves	Every file and config stays yours

Role types

Start with one managed AI employee

The strongest deployments begin with a single role that has clear boundaries, measurable output, and enough repeated work to justify continuous operation.

AI sales rep

A lead fills your form at 11pm. It's qualified, enriched and in your CRM with a follow-up sent before morning.

Form or inbox
Qualify + enrich
CRM + follow-up

For repetitive lead qualification, follow-ups, CRM updates and prospect research that should not depend on someone being online.

Inbound qualification
Lead enrichment
CRM updates and follow-up routing

AI support rep

Most common start

The same 20 questions get answered from your docs instantly. Edge cases go to your team with the context attached.

Ticket or chat
Answer from docs
Resolve or escalate

It answers standard requests from your knowledge sources, escalates anything unusual, and keeps your team on the harder tickets.

Customer response handling
Knowledge-based replies
Escalation and ticket triage

AI operations rep

Inputs collected, data moved between systems, status updates sent, without someone babysitting spreadsheets.

Inputs
Move between tools
Status report

For admin-heavy teams that need inputs collected, data moved between systems, actions triggered and status updates generated around the clock.

Internal process execution
Status reporting
Multi-tool workflow coordination

Handoff

What happens when it isn't sure

Low confidence or a policy rule sends the case to the person you choose, with the full conversation. The answer then goes into its knowledge so the same case is handled next time.

Request arrives
Ticket, chat, form or email
AI employee handles it
Answers, routes or updates systems
Branch: Low confidence or policy rule → your team
Handed over with the full context
Answer added to knowledge
Handled next time

Pricing

One role, two prices, no hiring

$2,000
One-time build fee: $500/mo
Management, monitoring, and improvement

Plus AI usage, estimated before you sign.

Scope my first role (30 min)

Hosting

Run it where you want

Self-hosted

Your cloud

Runs in: Your own infrastructure and accounts
Hosting control: Your team, directly
Built by: ATI Lab

Fully managed by ATI

ATI-managed

Runs in: A stack ATI hosts for you
Hosting control: ATI: runtime, updates, maintenance
Built by: ATI Lab

Managed model

ATI does not just build the role. We manage it.

Every month we review its conversations, fix wrong answers, update its knowledge when your products or policies change, and report what it handled.

Role-specific design instead of a generic chatbot
Integration with your actual tools and workflows
Managed monitoring, iteration, and performance tuning
Human review paths for edge cases and exceptions
A clear path from one AI employee to an AI-enabled team

Mission control

See what it did, change its rules, take over any case

With a mission control dashboard you see every conversation and action it took, can change its rules, and can take over any case. We scope the dashboard together with the role.

AI support rep · today

Live

Conversations

Where is my order #4471?Resolved
Change delivery addressResolved
Refund above policy limitWith your team
Invoice copy for MarchResolved

Rules

Escalate refunds above limit

Reply outside business hours

Offer discount codes

Handled vs escalated

HandledEscalated

Live visibility into current conversations, tasks, and workflow status
Controls for escalation rules, prompts, and operating boundaries
Review logs and performance trends for your AI employee
A central interface to manage one instance or multiple future roles

IllustrativeExample dashboard built from your role's data.

How it runs

Start with one job. Add the next once the numbers prove it.

Choose the role
We define one narrow business function with clear inputs, actions, escalation paths, and success criteria.
One job, clear limits
Build the employee
ATI connects the systems, sets up the logic around your workflow, and gives the role its boundaries and operating rules.
Connected to your tools
Manage performance
We monitor behaviour, review output quality, tune prompts and rules, and keep the employee useful instead of stale.
Monthly review
Expand capacity
Once one AI employee proves its value, we add adjacent roles or extend the same role across a larger workflow.
Next role when the numbers prove it

FAQ

Questions before you commit to the model

What is a managed AI employee?: A role-specific AI system that performs one recurring business function inside your workflow, with ATI handling implementation, management, and ongoing improvement.
Is this just a chatbot?: No. The role is built around execution inside tools and workflows, not just conversation. It can read inputs, make bounded decisions, update systems, and escalate when needed.
What happens when it doesn't know the answer?: It hands the case to the person you choose, with the full conversation, and we add the missing answer to its knowledge.
How long until it's live?: It depends on the role and how many tools it connects to. We agree a go-live date with you when we scope the role, so you know the timeline before the build starts.
Do we need a large company for this to work?: No. Smaller teams often benefit faster because one managed AI employee can remove a meaningful amount of repetitive operational work.
Can ATI manage it after launch?: Yes. That is part of the model. We do not just deliver a build and disappear. ATI manages performance, improvements, and workflow reliability over time.

Next step

Pick the role that eats the most of your team's week

Tell us which function is repetitive enough to hand over. We will scope the role, define its boundaries, and show you what it costs to run.

Estimate the ROI first Scope my AI employee