Systems you can control, not agents that do anything.
Noona is an AI worker that learns a recurring task once, then runs it every week across your email, files and tools. It asks for your approval before anything that matters.
30-minute call. We map your first three workflows together.
Across 5 cohorts and 3 organizations, 52 professionals identified the recurring work they want AI to help execute. The data is aggregated and anonymized at source.
Noona can collect the inputs, compare periods, identify patterns, draft the analysis, and stop for approval before the report is shared.
“Analyze the sales report, find patterns, and explain which campaigns performed best and why.”
Sales controller, D2C specialist, commercial teams.
Noona can run the research, organize the sources, draft the monthly report, and place it in the team's existing workflow.
“The competitor analysis report I prepare every month.”
Marketing, paid media, trade marketing.
Noona can search approved internal sources, draft an answer, update the ticket, and wait for human approval when needed.
“An AI agent that searches internal documentation and answers support tickets.”
IT, support, operations.
In 30 minutes, identify the task, tools, approval points, and first Noona specification.
Open a chat, describe the context, upload the file, explain the goal, fix the answer, copy the result, paste it somewhere else. Then do the whole thing again tomorrow.
A chat tool can answer a question. But your work was never a question. It's a routine with memory, tools and approvals, and nobody is holding it for you.
Show Noona the task the way you'd show a new hire. Share the file, the tool, the process. Once. No documentation, no scripting, no prompts.
Noona comes back with a draft, not excuses. You review it like you'd review any junior's first week: correct what's off, approve what's right.
Tell Noona what to change in plain language. "Next time, send this to finance first." It sticks. That's the whole training manual.
Start with one task. When Noona proves itself, hand over the next one. You decide what it can do alone and what always needs your sign-off.
No prompt engineering. No workflow builders. Just management, the skill you already have.
The strongest demand is not for another chat tool. It is for faster execution of recurring work across communication, research, reporting, support, meetings, and internal documentation.
Based on anonymized feedback from 52 participants across 5 cohorts and 3 organizations. Time figures are self-reported estimates.
It learns from instruction and feedback, like anyone you've ever onboarded.
It asks for approval before anything sensitive, tells you when it doesn't know, and never acts outside the boundaries you set.
Every action is visible, reviewable, and reversible. You always know what it did and why.
You delegate outcomes, not keystrokes.
Claude Code is built for teams that write software. Noona is built for managers who delegate work.
Autonomy without oversight isn't a feature, it's a liability. Noona works the way a trusted employee does: with a clear mandate and your final word.
Ideal if you're in leadership, HR, L&D or operations and want to prepare your people and scale AI adoption across the company.
Run the business, not the busywork.
Onboarding, training, adoption at scale.
Accurate, standardised work.
Pipeline, offers, follow-ups.
Briefs, campaigns, always on brand.
Founders and entrepreneurs who need an assistant they can trust.
You stop explaining yourself from zero, every day.
Things actually get produced, not just discussed.
Priorities are kept at the surface, not buried in noise.
Research, copy, reports and materials ship faster.
You approve what matters; Noona does the heavy work.
Watch a real run: Noona joins a stack, loads the skills for a role, and runs one live, stopping for your approval where it matters.
Every task starts and ends with you.
Next time it does the work and hands it to you.
The more it runs, the better it gets.
Every task starts and ends with you.
You walk Noona through the task, one time.
Next time it does the work and hands it to you.
Once it's right a few times, it runs without being asked.
It catches mistakes before they reach you.
The more it runs, the better it gets.
The first Noona workflow should not be invented in a workshop. It should come from work your team already performs every week or every month.
In the measured cohorts, teams most often identified recurring opportunities in email and communication, customer responses, research, support, spreadsheets, meetings, internal documents, and reporting.
Leave with the first role Noona will hold.
A plain 5-minute read: how an AI worker differs from chat tools and copilots, and how to put your first one to work, the right way.
Not sure where to start? This 6-minute read shows the five tasks worth handing over first, and the ones to keep for later.
The five reasons AI projects stall, none of them the model, and how to start so yours actually sticks.
Agents like Claude Code or Hermes can build and run real systems. But handing an agent your whole business, unstructured, doesn't buy autonomy. It buys runaway costs, fragile workflows and bugs nobody can trace.
So we use agents as builders first. We split the work into clear parts, each with its own context, permissions, inputs and outputs. The agent only touches what a task needs, never your whole operation. Think of a website with a clear map: it knows exactly where to work and what it's allowed to change.
Only once the foundation is solid do we switch on autonomous, scheduled and multi-agent work. Not every task needs an agent: some need plain software, some need you. We use agents only where judgment and adaptation actually pay off.
We don't sell agents that do anything. We build systems you can control.
52 professionals documented concrete AI use cases across sales, finance, marketing, HR, IT, support, and operations.
85% reported time savings. Average estimated saving among respondents who quantified it was 5.4 hours per person per month.
The strongest use cases included sales analysis, competitor research, support answers, reporting, meeting follow-up, procedures, and internal documentation.
These figures measure AI adoption and work opportunities identified in training and workflow discovery. They are not presented as performance results produced by Noona.
Bring a recurring task your team already performs. We will map the trigger, inputs, tools, decisions, approval points, and required output.
Choose work that repeats weekly or monthly.
Define the tools, data, actions, exceptions, and approvals.
Compare the old process with the Noona workflow.
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