Switching agent platforms mid-campaign feels like changing tires while the car's still moving. I get it. Most marketing agencies I've worked with put off migrating from Agent.ai for months β not because the new platform is worse, but because nobody wants to break a working lead-routing flow during a client's product launch. Here's the good news: moving to an ai agent platform like Aiinak is usually a 1-2 week job, not a quarter-long project. The bad news? The agencies that rush it skip the parallel-running period and pay for it in week three.
This guide walks through how to do it without dropping a single client deliverable. I've structured it the way I'd structure a real deployment β planning first, then data, then people, then a safety net, then go-live.
Why Marketing Agencies Outgrow Agent.ai
Agent.ai is genuinely good at what it does. It's a solid place to build and chain autonomous ai agents for content tasks, research, and lightweight automations. For a freelancer or a two-person shop, it's often enough.
But agencies hit a ceiling. The common one: Agent.ai agents are great at suggesting and generating, less great at doing. Your agent drafts the outreach email β then a human still has to send it, log it in the CRM, and book the follow-up. For an agency running outreach across 15 clients, that handoff tax adds up fast.
The other ceiling is operational. As you scale, you want agents that actually run client operations end-to-end β pulling a lead from HubSpot, qualifying it, sending the sequence, updating the deal stage, and flagging the hot ones to a strategist. That's where agencies start shopping for a platform built around ai agents for business that perform real actions, not just text output.
Aiinak's pitch sits exactly here. Its agents send the email, update the CRM, process the invoice, book the meeting. That's the gap most agencies are trying to close. Whether it's worth $499/agent/month to you depends on how much of that manual handoff is currently eating your team's hours β and I'll come back to that math.
Week One, Days 1-3: Planning and Inventory
Don't migrate anything yet. First, write down what you actually have. Most agencies are shocked by how many half-finished agents are sitting in their Agent.ai workspace.
Build a simple inventory spreadsheet with four columns:
- Agent name and purpose β what does it do, for which client?
- Trigger β manual, scheduled, or event-based?
- Integrations it touches β HubSpot, Salesforce, Slack, Google Sheets, etc.
- Keep / rebuild / retire β be honest here.
That last column matters most. In nearly every migration I've seen, 30-40% of existing agents get retired because they were experiments nobody uses. Don't port your clutter. A migration is the best free audit you'll ever run.
Then map your integrations against Aiinak's 25+ supported connections β Salesforce, HubSpot, QuickBooks, Slack, Zoom, and the rest. If a client's stack uses something exotic, find that out now, on day two, not on go-live morning. This is the single most common pitfall: discovering a missing connector after you've already told the client you've switched.
Finally, pick your pilot. Choose one client or one internal workflow to migrate first. Lead qualification is a great pilot because it's high-volume and easy to measure. Resist the urge to move everything at once.
Days 4-7: Data Migration and Agent Rebuild
Here's the part people dread that's actually the easy part. You're not migrating a database. You're recreating workflows.
Agent.ai and Aiinak don't share an export format, so there's no one-click import β and honestly, you wouldn't want one. Rebuilding forces you to clean up logic you'd otherwise carry over blindly. Aiinak's agents deploy in three steps with no coding, so rebuilding a qualification agent that took an afternoon to wire up in Agent.ai usually takes under an hour the second time around.
Your real data migration work is three things:
- Connect the integrations. Authenticate each tool the agent needs. Do this once per client workspace and test the connection with a dummy record before you trust it.
- Move your prompts and instructions. Copy the system prompts, tone guidelines, and qualification criteria you've refined. This is your actual IP β the months of tuning that make an agent sound like your agency. Don't rewrite from scratch.
- Migrate reference data. If your Agent.ai agents pulled from knowledge bases, FAQ docs, or brand guidelines, load those into Aiinak's Drive with its RAG search so agents can retrieve them.
One practical tip from deployments I've seen: rebuild agents in a sandbox state first, where they log what they would do without actually doing it. You want to watch an agent decide to send an email before you let it send one to a client's prospect. Aiinak lets you run agents in this kind of supervised mode β use it.
Days 7-10: Team Training and the Parallel-Running Period
This is the phase agencies skip, and it's the phase that determines whether the migration sticks.
Run both platforms at the same time for at least three to five business days. Your Agent.ai flows keep running for the client. Your new Aiinak agents run alongside them, doing the same work in parallel. Then you compare outputs. Did the Aiinak qualification agent score the same leads as your old one? Did it catch the edge cases? Where did it diverge, and was the new behavior better or worse?
This parallel period is your insurance policy. It's the difference between finding a problem in a controlled comparison versus finding it when a client asks why a hot lead went cold. Budget for it. Don't let an eager account manager flip the switch early.
On training: the learning curve is real but short. Most agency teams are productive on Aiinak within a few days because the no-code builder is genuinely no-code. The mindset shift is bigger than the tool shift. Your team is used to agents that produce drafts they review. Now they're supervising agents that take actions. That's a different relationship β more oversight on guardrails, less on individual outputs.
Practical training steps that work:
- Run one live build session per team, screen-shared, rebuilding a real agent together.
- Document your agency's guardrails β what agents may do autonomously vs. what needs human sign-off.
- Assign one internal "agent owner" per client account who watches the logs during the first two weeks.
The Real Cost Math: Agents vs. Manual Handoffs
Let's talk numbers, because $499/agent/month sounds like a lot until you put it against what it replaces.
Consider a typical scenario: an agency running outbound lead qualification for clients, where a coordinator spends roughly two hours a day pulling leads, scoring them, updating the CRM, and triggering sequences. That's about 40 hours a month of work that an autonomous agent handles end-to-end. At even a modest loaded labor cost, you're well past the agent's monthly price β and the agent works nights and weekends without a Slack message about being underwater.
Aiinak's own framing is that agents run roughly 90% cheaper than the equivalent headcount, and McKinsey has estimated that a large share of marketing and sales tasks are technically automatable with current technology. I won't pretend every agency hits those numbers β your mileage depends entirely on how much manual handoff you're carrying today. Agencies that report the strongest results are the ones drowning in repetitive coordination work, not the ones whose agents only draft copy.
The pricing tiers matter for planning. Starter is $499/agent/month for a single agent β fine for piloting. Business is $2,499/month for up to five agents, which is where most multi-client agencies land. Enterprise is custom. My advice: pilot on Starter with one agent, prove the time savings on one client, then scale to Business once the math is undeniable. The 14-day free trial means your pilot's first two weeks cost nothing, which conveniently covers your entire parallel-running period.
Go-Live, and What You'll Actually Miss From Agent.ai
Go-live should be boring. If you ran a real parallel period, go-live is just turning off the old agents β one client at a time, never all at once. Keep your Agent.ai workspace active and read-only for two more weeks as a rollback option. Then decommission it.
Now the honest part, because no migration guide that pretends the new tool is perfect is worth reading.
You'll miss some things about Agent.ai. Its community and template marketplace are mature, and if you relied on community-built agents as starting points, you'll be building more from scratch on Aiinak. Agent.ai's lighter footprint also makes it feel snappier for quick, throwaway experiments β Aiinak is built to run operations, not to be a sketchpad. And if your agency's needs are genuinely small β a couple of content agents, no real action-taking β Aiinak may be more platform than you need, and the price reflects that.
Here's what Aiinak gives back. Agents that complete the full loop instead of handing work back to your team. Built-in enterprise apps β email, CRM, ERP, helpdesk β so agents aren't just bolted onto your stack but operate inside one. 24/7 operation across every client account. And the action layer that turns "my agent drafted this" into "my agent did this," which is the entire reason agencies migrate in the first place.
One limitation worth naming plainly: autonomous ai agents still aren't a replacement for strategic judgment. They'll qualify the lead and book the call. They won't decide your client's positioning or read the room on a tense renewal. Keep humans on strategy. Put agents on execution. Agencies that get the split right are the ones still happy six months post-migration.
If you're ready to test it on a real workflow, start small. Deploy Your First AI Agent on one client's lead qualification, run it in parallel for a week, and let the comparison make the decision for you. That's the whole migration in one sentence β pilot, compare, scale. Most agencies are fully moved within two weeks, and the only thing they regret is not doing it a quarter earlier.
Originally published on Aiinak Blog. Aiinak is an AI agent platform that runs your entire business β deploy autonomous agents for Sales, HR, Support, Finance, and IT Ops.
