Theona is the platform where a team keeps its agents: built once, shared with everyone, running inside the tools people already use. That hasn’t changed.
What’s new is that our team now works inside yours. We come in for a pilot, spend a few weeks in the routine of how your people get things done, and build the agents around what we find. By the end of the pilot your team is working AI-native: the daily routine runs with agents inside it, and our part of the work keeps shrinking after that.
We start with the routine and not with the agents, because every team has two versions of its process. One lives in the onboarding doc: six clean steps, one owner per stage. The other is the path worn into the carpet: the colleague everyone messages when the form breaks, the approval that takes three days because it happens over email. Automate the first version and you get agents nobody opens. The second version is where the hours are.
Phase 1: We Learn How Your Team Works
We spend the first weeks with your team and with the traces its work leaves behind: conversations, meeting recordings, tickets, the handoffs between one tool and the next. Theona reads across all of it, and we turn what comes out into a map. Steps, owners, and the points where work waits for someone.
Then we review that map with your people. This is the part that earns its keep, because the first draft is always wrong in ways only your team can correct. Two or three rounds and it matches what people recognize.
What you get at the end of Phase 1:
- A map of how your team works, drawn from what people do day to day
- The top three workflows ranked by what an agent would return
- The time and cost each one carries today
- A recommended scope for Phase 2
Some of what surfaces has nothing to do with agents. A step is slow because a feature you already pay for was never turned on. We say so. A map that only ever recommends more automation is a sales document, not a map.
By the end of Phase 1, you know which work is worth automating and what it costs you today.
Phase 2: We Build the Agents Into Your Week
We build the agents into the week your team already has. Nobody gets a new app to learn. An agent sits in the channel your team is already in, works with the CRM, the tracker and the calendar they already use, and answers in the same thread.
Every agent starts in draft mode: it does the work and stops before the last step, and a person reads the result before anything leaves the building. It’s the arrangement you’d give a new hire, and you stop reading once you no longer need to. When your team trusts an agent, you let it run alone. That decision is yours, and you can take it back.
How we work together during the build:
- A weekly demo call, thirty to forty-five minutes, where you see what runs
- An async channel between calls for anything that can’t wait a week
- A final week reserved for testing and stabilization rather than new features
The workspace and the usage for the pilot are included, so the price doesn’t move depending on how much the agents work.
By the end of Phase 2, the agents are running in your tools, and your team decides how much they run alone.
Phase 3: Your Team Takes Over
An agent built around a process is only as current as that process. Your team changes a form, adds a stage, drops a tool, and an agent that was right at launch is quietly wrong two quarters later. Automation projects tend to fail here, months after the build, when everyone has stopped watching.
So Phase 3 has no end date, and it’s the phase where we deliberately become less necessary. We’re hands-on right after launch and step back as your people take ownership.
What ongoing looks like:
- A monthly review of how the agents perform and where they should adapt
- A quarterly session on what to map and build next
- New agents as new work becomes worth handing over
The second wave of use cases usually comes from your team, not from us. Once people watch an agent take over one part of their week, they start spotting the next one and build it themselves. That’s when a team stops running a pilot and starts working AI-native.
What This Looked Like for a Recruiting Team
The team was hiring for an AI Engineer role. Between one hundred fifty and two hundred applications arrived every week, and the team could read forty to sixty of them by hand. The rest sat in the pile unopened, which is a different problem from rejecting them.
Weekly hours, before and after:
- Resume screening: 5 hours to 0
- CRM and document work: 6 hours to 2
- Interview processing: 7 hours to 1
The hours were not the number that mattered most. Every application now gets read and ranked, so strong candidates stop falling off the bottom of the pile. Interview feedback lands in an hour instead of two or three days. The path from application to offer went from twenty-five days to ten, which decides who gets to make a good engineer an offer first. Total weekly load went from eighteen hours to three, and the freed hours went into sourcing.
The same shape shows up in other functions. In an inbound sales pilot at a developer learning platform, agents took over enrichment, CRM records, first-touch email and booking alerts. First contact with a new lead now happens in under three minutes, and demo calls booked rose by thirty-five percent.
What the Platform Gives You
The pilot is our people. What holds it together afterwards is the platform, the same one whether we build the agents with you or your team builds them without us.
Agents connect to the tools your company already pays for and live in Spaces, grouped by team or function, along with the knowledge each group works from. Share a Space and everyone in it can use those agents on their first day. Run history shows what ran, when, and what it did, so nobody has to trust a black box.
The map from Phase 1 stays there too. We don’t hand it over and walk away from it: the platform keeps it as the picture of how your team works, and every run the agents do sharpens it. The agents change over the years. The map underneath them stays current.
Agents also start themselves, on an event or a schedule, so the work doesn’t wait for someone to remember it.
Access and Approvals
Every security review asks two questions: what can the agent reach, and what can it do without asking. An agent never has more access than the person who connected the tool, and anything sensitive or irreversible waits for a human to confirm it. Every run is logged and open for review.
Your data is never used to train models. Theona is GDPR compliant, the SOC 2 Type II audit is in progress, and the documentation is public at trust.theona.ai. Deployment inside your own infrastructure is available as an Enterprise add-on. The longer version is in AI agents and corporate security.
Start With One Process
There are two ways in, and which one fits depends on where your team is.
If your processes are still taking shape, or you want to see it work before anyone else is involved, start free, build an agent for something you do every week, and put it in a Space your team can reach. Plenty of teams get where they need to go this way.
The pilot is built for organizations that already have processes worth mapping: a thousand people or more, in ops-heavy work like sales ops, HR, support or marketing ops, often with AI subscriptions already scattered across departments. If that sounds like your company, bring us one process that feels slow or manual and we’ll start there. The pilot stays narrow on purpose: one that takes on the whole company finishes late and proves nothing. And if agents turn out to be the wrong answer, we’ll tell you, and the map is yours either way.
Book a free audit and we’ll show you what your first weeks would look like.