Sistava is an AI workforce platform where solo founders hire AI employees to run their business around the clock. Each AI employee has a specific role like sales, marketing, or customer support, with real tool integrations, persistent memory, and the ability to work inside your existing apps like Slack, Gmail, and HubSpot.

What is an AI employee?

An AI employee is an autonomous AI agent with a defined role, persona, skill set, and tool access. Unlike a chatbot that only answers questions, an AI employee takes on recurring work like writing emails, qualifying leads, answering support tickets, and publishing content, and it works on its own around the clock without being prompted each time.

How is Sistava different from project management software?

Sistava is not project management software. You hire AI employees who do the work, not a tool that tracks work done by humans. Your AI employees run sales outreach, write marketing content, answer support tickets, and handle operations on their own, without constant supervision.

How much does Sistava cost?

Sistava has a free plan you can start without a credit card, plus paid plans that scale with how much work you hand to your AI employees. See the pricing page for current plans.

What can AI employees do on Sistava?

Your AI employees take on the recurring work that runs a business: qualifying and reaching out to leads, writing and publishing marketing content, answering support tickets, and handling day to day operations. Each one comes with a role and skill set, so it can start working the day you hire it.

Sistava is built for solo founders and small teams who need to run sales, marketing, support, and operations without hiring a full human team. It gives you the equivalent of a growth team you can hire in minutes.

A 90-Day AI Transformation Plan for Small Teams

Guide — 2026-08-02 — by Mahmoud Zalt

A realistic 90-day plan to bring AI Employees into a small team: start with one role, prove value, then expand across sales, support, and ops.

Most AI transformation plans fail the same way: they try to change everything at once. A small team reads about the future, buys five tools, assigns nobody to own them, and three months later the tools sit unused while everyone goes back to doing the work by hand. The problem is never the technology. It is the rollout. Real change on a small team happens one role at a time, with a clear owner and a visible win, and then it spreads because people saw it work, not because a memo told them to adopt it.

This plan uses AI Employees rather than a pile of point tools, which keeps the change simple. You hire a pre-built role, brief it in one paragraph, and it works the same day, so you spend the 90 days proving value instead of building infrastructure. The structure below is deliberately unambitious in month one and only expands once the team trusts the first result. That sequencing is the whole trick: adoption is a trust problem, and trust is earned with one clear win before you ask for a second.

At a Glance

1: AI Employee you start with in month one
49/mo: Sistava entry plan to begin the plan
90 days: From first hire to running habits
Plain English: How the whole team briefs and corrects it

Month one: prove value with a single role

The first month has exactly one goal: make one AI Employee save real, countable hours on one job. Do not pick the most exciting use case. Pick the most painful repetitive one, the task someone on your team quietly dreads every week. That could be answering the same support questions, drafting outbound emails, or writing the weekly report nobody has time for. A boring task with a clear owner beats a glamorous one with none.

Give one person on the team ownership of the new hire. Their job is to brief it, read the first outputs, correct it, and measure the hours it gives back. By the end of month one you want a simple, honest number: this role saved us this many hours a week, and the output quality is good enough that we trust it. That number is the entire foundation for the next two months, because it turns AI from an idea the team argues about into a result they have seen.

Resist the urge to expand early even when month one goes well. The most common failure I see is a team that gets one quick win and immediately hires four more roles nobody has time to calibrate. Momentum is real, but calibration is what makes an AI Employee trustworthy, and calibration takes attention. Let the first role become genuinely reliable and let the team feel the relief of not doing that task anymore. That relief is what makes them want the second role, and wanting it is far better than being told to use it.

Month two: calibrate and add the second role

Month two does two things. First, it hardens the role you started with: tighten the brief, add the edge cases you hit, and reduce how often you have to correct it until it runs with a light touch. Second, it adds a single new role in the next-most-painful area, run the same way, with an owner and a target number. Two roles is plenty for a small team in the first 60 days, and adding them one at a time keeps each one properly calibrated instead of half-trained.

Benefits

Sales outreach

Research leads, draft personalized first touches, and log every contact so the pipeline stays honest.

Customer support

Draft answers to common questions and escalate the ones that genuinely need a human.

Marketing content

Turn your notes and updates into posts, newsletters, and drafts in the team's voice.

Operations and reporting

Gather numbers, prepare recurring reports, and keep routine admin from piling up.

Month three: connect the roles and lock in the habits

By month three you have two roles the team trusts, and the goal shifts from proving value to making it permanent. Connect the roles so work flows between them: the sales Employee hands qualified leads to the founder, the support Employee flags recurring issues to the product owner, the reporting Employee pulls from both. Then write down the light process around them so a new team member could step in. Habits that live only in one person's head disappear when that person is on vacation.

The 90-day sequence at a glance

Days 1 to 30: one role, one owner, one number — Hire the AI Employee for your most painful repetitive task and prove the hours it saves.
Days 31 to 45: harden the first role — Tighten the brief, add edge cases, and reduce corrections until it runs with a light touch.
Days 46 to 60: add the second role — Hire one more Employee for the next-worst pain point, with its own owner and target.
Days 61 to 75: connect the roles — Let work flow between the Employees and route the human decisions to the right person.
Days 76 to 90: lock in the habits — Document the light process, review the hours saved, and decide the next role to add later.

The reason this 90-day shape works is that it treats AI adoption as a people change, not a software install. Each month asks the team to trust one more thing, and each ask is backed by a result they already saw. By day 90 you are not hoping the tools get used. You have two reliable AI Employees doing real work, a team that chose to rely on them, and a clear, calm answer to what to automate next. That is a transformation that sticks, because it grew instead of being imposed.

One honest caveat: 90 days gets you two solid roles and durable habits, not a fully automated company. That is the right expectation for a small team, and it is a feature, not a shortfall. The teams that try to automate everything in a quarter end up trusting nothing. The teams that add one reliable role at a time end up, a year later, with a workforce of AI Employees they actually depend on. Slow is smooth, and smooth is what compounds.

Frequently asked questions

FAQ

Why start with only one AI Employee instead of several?

Because adoption is a trust problem, and trust comes from one clear win, not five half-calibrated tools. A single role with an owner and a measurable hours-saved number gives the team proof. That proof is what makes people want the next role rather than resist it, which is why the plan expands only after month one succeeds.

What kind of team is this 90-day plan for?

It is written for small teams and solo founders without a technical hire. Because AI Employees are pre-built and briefed in plain English, no one needs to code or manage infrastructure. The owner of each role just needs to describe the job well and read the first outputs, the same skills a good manager already has.

How much should we budget for the plan?

You can start the whole plan on Sistava's entry plan at 49 per month with credits bundled in and no per-seat fee. Small teams often run the first two roles on a modest plan and only move up as usage grows. The budget question is smaller than most transformation plans assume.

What if the first role does not save enough time?

Then you picked the wrong task or the brief needs work, and month one is exactly when you find that out cheaply. Tighten the brief, add the edge cases, or switch to a more repetitive task. The point of starting with one role is that a miss costs you a few weeks of learning, not a company-wide rollout.

Can the team adjust the AI Employees as we go?

Yes. Every Employee is briefed and corrected in plain English, so the team refines each role as they learn. Adding a step, changing the tone, or handling a new edge case is a short conversation, not an engineering task, which is what lets a non-technical team own the whole plan.

The plan is deliberately simple: one role, prove it, calibrate it, add a second, connect them, and lock in the habits over 90 days. It works because it respects how small teams actually change, through visible wins and earned trust rather than sweeping mandates. Pick your most painful repetitive task, give one person ownership, and hire a single AI Employee this week. In three months you will not have a slide about transformation, you will have two reliable teammates doing the work and a team that chose to keep them.