For a marketing team in late 2026, an agent builder is mostly the automation tool it already pays for, with an agent step inside. Zapier is folding Agents into ordinary Zaps, Make shipped a new agent app in February, and ChatGPT lets a Business workspace share agents like files. Building one takes an afternoon; running it for a year is the part nobody demos.
Empact Partners works as a go-to-market consultancy inside B2B software companies, and part of our RevOps work is building the agents their marketing and sales teams run, from lead routing to replies. Our first question of any builder: with no setting changed, does the agent ask before it sends?
On 27 October 2026 we read seven builders’ documentation and pricing for four things: whether the agent asks before sending, who can run it without editing it, which apps it reaches, and what a month costs. Two ask first out of the box, four run straight through, and one does not say. Relay.app, known for approvals, shut down in September.
| Tool | Best for | Asks first out of the box? |
|---|---|---|
| Zapier | Agent steps in the lead Zaps you already run | No, a per-tool switch |
| ChatGPT | Teams already on ChatGPT Business | Yes, for write actions |
| n8n | One technical owner | No, a step to add |
| Make | Operators who run, not edit | No built-in step |
| Lindy | Inboxes and meetings, in Slack | Yes, for outside actions |
| Relevance AI | A sales agent built with the vendor | Per tool, default unstated |
| Gumloop | Research and data agents | No, “Always allow” |
1. Zapier
Best for: agent steps inside the lead automations a team already runs across its apps.
Zapier is the automation tool most marketing teams already pay for, and its agents now live inside Zaps. The standalone Agents product is being migrated into AI by Zapier, a step that reasons and calls tools in the middle of a normal Zap. No shut-off date is set, so anyone shopping for “Zapier Agents” is shopping for this.
For a lead agent it puts approval, limits, and a record in one place. A tool can require approval before it runs, and a run that passes its task limit pauses for review: 75 tasks by default, adjustable up to 500.
Zap history records every run and the tools it called. An admin can also require an approval before any Zap with an AI step goes live.
Two things bite after handover. The approval switch ships off, so an agent handed over without it sends on its first run. And the step bills in tasks, 3 for the step and 3 per tool call on an Advanced model, so an agent that looks a lead up, replies, and logs it spends 12 tasks per lead.
Pricing
Pros and cons
What Reddit and Capterra reviewers say
“I prefer Zapier because as a digital marketer, I would like to spend time more on “doing with the things” rather than working with developers on N8n and going through a long process, testing, deployment, bug fixes etc technical work.” — u/CorrectCake8334, r/hubspot, Jan 2026
“Of course even worse is when they get it to do something, but instead of updating 1 record, they update 10000 and suddenly is my emergency to fix.” — u/misanthrope2327, r/zapier, Oct 2026
“Everything is metered per task, and a task is any single step that runs, so a five step Zap burns five tasks every time it fires.” — SDE in information technology, Capterra, Sep 2026
Standout feature: Require approval before running
One toggle per tool decides whether the agent may act alone. Leave it off for lookups and turn it on for anything that sends, updates, or deletes, and the run waits for a person before that one step. For a lead agent that means the CRM lookup and the scoring run freely and the reply waits.
Verdict: the builder to pick if your leads already move through Zaps and someone will switch the approval on before handover. Skip it if the person approving will not answer an email within the hour, or if the agent will make hundreds of tool calls a day on Premium models.
2. ChatGPT Workspace Agents
Best for: a team that already works in ChatGPT Business and wants shared agents with a chat-only seat.
Workspace agents are OpenAI’s no-code builder inside ChatGPT Business and Enterprise, launched in April as a research preview. You describe the job, the builder drafts the agent, and you connect apps, files and skills. The agent then runs in ChatGPT, on a schedule, from an API call, or in a Slack channel.
Its defaults lean toward the person running the agent. Write actions are set to Always ask, so it stops before it sends, updates, or posts unless the builder turns that off. Sharing separates running from editing: Can chat lets someone use the agent and read its setup, Can edit lets them change and republish it, and sharing a link makes nobody an editor.
Workspace agents are still a research preview. In the one first-hand report we found, an agent kept sending owners the same follow-up actions after its user had cleared them.
An agent-owned connection lets everyone who runs the agent act through that one account, and OpenAI’s own help page warns against connecting a personal one. And a month of runs is not in the seat price: agents bill tokens against the workspace’s credits.
Pricing
Pros and cons
What Reddit and G2 reviewers say
“Im kinda getting at a point where im losing hope since it doesnt do anything consistently. For example, i would clear the action ledger and it would still continue to send the same action to owners despite telling it these were cleared.” — u/Illustrious-Theory-2, r/AI_Agents, May 2026
“I reactivated a ChatGPT business subscription expecting my existing workspace to be restored. Instead, the system created a new workspace and separated me from my historical chat data.” — G2 reviewer, Jan 2026
Standout feature: Write action safety
Every app connection carries a write action setting, and it starts at Always ask. Below it, safety constraints narrow what the app may do at all, written in plain language: send email only to your own domain, read only one document. For a team handing an agent to people who did not build it, that pairing is a seatbelt fitted at the factory.
Verdict: the builder for a team that already lives in ChatGPT and wants defaults that ask first for whoever runs the agent. Skip it if the apps your lead agent needs are not among the ones your workspace can enable, or if finance needs a fixed monthly number.
3. n8n
Best for: a team with one technical owner who builds, and wants runs priced per execution or kept on its own servers.
n8n is a visual workflow builder with an AI Agent node and an open-source edition. That Community Edition runs free on your own servers, and the cloud plans start at $20 a month billed annually. Most marketing teams meet it through whoever on the team, or outside it, is comfortable with webhooks.
n8n sends approval requests to Slack, Microsoft Teams, Gmail, Outlook, or its own chat. Any tool an agent uses can go behind a human review, so the approver says yes without logging in to n8n.
Pricing counts workflow executions, not steps. That makes an agent with many tool calls cheaper here than on a per-task meter.
Whoever runs it gets the builder’s view. The reviewer sees the tool’s name and its raw parameters unless the builder writes a readable message. A read-only seat, for the marketer who should run a workflow and never edit it, is an Enterprise role. And error handling works only as well as somebody built it.
Pricing
Pros and cons
What Reddit and G2 reviewers say
“make/zapier bill per operation, n8n bills per execution (a whole workflow run = 1, no matter how many steps). a workflow that loops over 500 records costs the same as one that processes 1.” — u/Travis_Flywheel, r/n8n, Jul 2026
“Error handling in n8n is, um, disappointing and highly manual to account for this gap.” — r/hubspot, Jan 2026
“The learning curve can also be significant for non-technical users, especially when starting to work with APIs, expressions, JSON, and error handling.” — Presidente at a small business, G2, Aug 2026
Standout feature: Human review for tools
The review step sits on the agent’s tools, not on the whole workflow. Put the email tool behind it and the agent drafts, reasons, and looks things up on its own, then pauses on the one action that leaves the building. The request goes to whichever channel the approver lives in.
Verdict: pick it when one person owns the workflows and you want approvals in Slack or Teams at a price that does not climb with every tool call. Look elsewhere if nobody on the team will ever open the canvas, because below Enterprise there is no role that can see a workflow without being able to change it.
4. Make
Best for: teams that want people to start, stop, and schedule agents without being able to edit them.
Make is a visual automation builder with 3,500+ apps, and its AI Agent app, released on 2 February and still in open beta, puts an agent inside a scenario next to ordinary modules. The Reasoning panel shows each decision the agent made, step by step, on the canvas.
Its most useful card for a handed-over agent is a role. Team Operator lets a person view, switch on, stop, and schedule scenarios without editing the logic inside them, which is the job of whoever runs a lead agent. Team Monitoring can view and cannot switch anything.
Make names the weak spot itself. Its own introduction to agents tells you to give them tasks you would trust an intern with and to keep them away from sensitive data.
The approval its docs describe is a Slack message you reply to, built by hand. The one practitioner we found who built the same lead agent on Make, Zapier, and n8n named Make’s approval gate as the problem.
Pricing
A module action is one credit. An agent on Make’s own AI provider adds credits for its tokens.
Pros and cons
What Capterra and G2 reviewers say
“The simple UI/UX of make, is helpful for non technical person to understand and create workflows without any issues and hassle.” — Lead, tech and AI automation, Capterra, May 2026
“Only thing is, when one step fails it sometimes stops the whole scenario, and debugging takes a bit too long. Also hit the operation limit faster than I thought” — Community manager in telecommunications, Capterra, May 2025
“I don’t know if I’d say anything doesn’t work, but I’d like automatic suggestions on how to use my credits more carefully.” — Verified user at a mid-market company, G2, Oct 2026
Standout feature: Team Operator role
Team Operator sits between the usual editor and viewer. It can switch a scenario on, off, or onto a schedule, and it cannot touch the logic inside, which is the seat a handed-over agent needs.
Verdict: right for a team that keeps one builder on hand and wants everyone else running agents without the power to change them. Not yet for a lead agent that sends on its own, until Make ships an approval step.
5. Lindy
Best for: one assistant in Slack that handles everyone’s inbox, meetings, and follow-ups.
Lindy has turned from an agent builder into an assistant the whole team shares. It lives in Slack, connects each person’s email and calendar, drafts replies in their voice, joins calls, and runs routines you describe in plain language. Skills and routines are where the building happens.
Approvals are on by design. Anything with outside impact waits for approval (an email, a ticket update, a post in another channel, a published document), while read-only lookups run freely, and email drafts land in the person’s own drafts folder. Credits are pooled across the workspace, and an admin can cap any teammate’s month.
The bill grows with your Slack. A person takes a seat the first time they mention Lindy in your Slack, gets a free week, and stays billed until an admin removes them.
A teammate’s credit limit stops usage only after it is crossed, so the task that crosses it still finishes. And Lindy is built around people’s inboxes, not around a lead moving from a form into a CRM.
Pricing
Pros and cons
What G2 reviewers say
Every independent review we could find predates Lindy’s move into Slack, so read these as notes on the company, not on today’s product.
“Considering how many permissions and integrations the platform demands across email, calendars, and cloud storage, I wouldn’t trust this company with any personal or sensitive data.” — Market research intern at a mid-market company, G2, Nov 2025
“Additionally, the price, while justified by the ROI, can become a limiting factor for small teams as you need more “Lindies” or monthly tasks.” — Admin at a small business, G2, Oct 2025
Standout feature: Credit limits per teammate
An admin sets a monthly credit ceiling for each person from the members table, so one enthusiastic teammate cannot spend the whole team’s pool by Wednesday.
Verdict: the assistant to give a marketing team that works in Slack and wants nothing sent without a person’s yes. Skip it as the home of a lead-routing agent, and budget it per person, since everyone who mentions it becomes a seat.
6. Relevance AI
Best for: a go-to-market team buying a ready-built AI sales teammate, set up with the vendor.
Relevance AI sells agents and teams of agents for sales, marketing, and support. You build them in its no-code builder or buy them ready-made: its pricing page offers a business development representative (BDR) agent through sales.
An embedded deployment team gets you live and then trains your people to build. The pricing page lists one plan, Enterprise, and answers how to start with “Talk to our sales team.”
The controls suit a team where most people only run agents. Each tool is set to Autopilot or Human in the Loop. A project Member can run agents without changing them, and the Chat role uses agents only through Relevance Chat, with no access to the builder.
Price is the first gap. There is no public price to put in a budget, so the number arrives in a sales call.
Relevance AI’s own documentation says that sharing an agent as a Chat UI, a chat widget, a Task UI, or a template makes it publicly accessible. That is no way to share an agent with CRM access. We found no independent Reddit user with recent first-hand use.
Pricing
Pros and cons
What G2 reviewers say
“I would like more governance controls and admin configuration controls for the administration team.” — Manager, sales development, at an enterprise, G2, Sep 2025
“The onboarding experience can be a little confusing. I spent a bit of time just figuring out where things were. But once you get the hang of it it’s very intuitive.” — Product marketing manager at a small business, G2, Mar 2025
Standout feature: Approval Mode
You set Approval Mode for each tool. Autopilot lets the agent use that tool freely; Human in the Loop makes it ask first, with the request shown in the agent’s interface. Paired with run-only roles, it lets a sales team use an agent whose riskiest tools nobody on the team can switch to autopilot.
Verdict: the one to call if you want an outbound or lead agent built with the vendor, and roles that keep most of the team on the run side. Wait if you need a price before the first meeting.
7. Gumloop
Best for: marketing-ops research and data agents, with approval rules written per app.
Gumloop started as a workflow builder for marketing and ops teams and now centers on agents: you give one connectors, skills and company knowledge, and it works in chat, in Slack or on a trigger. Its pricing page lists the old Workflows as legacy.
Its approvals are the only ones here that take conditions. Each connector can be set to always allow, ask each time, ask for writes and deletes, or never allow. App Rules then add conditions to a single call, such as asking only when an email goes outside your domain. Approval cards show a readable summary and can arrive as a Slack DM.
Every connector starts at “Always allow”, so the approvals exist only if the builder set them. Credits are billed at the list cost of models, compute, and paid tools, plus an 8% orchestration fee. Unused credits do not roll over, and when the month’s credits run out, the agents stop until someone turns on pay as you go.
Pricing
Credits are indexed at half a cent each, and the orchestration fee rises to 16% if you bring your own model keys.
Pros and cons
What Reddit and G2 reviewers say
“I spoke to their team and they “highly discourage” their workflow feature and just want you to build agent loops around tools.” — u/DisplacedForest, r/AI_Application, Mar 2026
“The platform is much simpler than n8n and significantly more flexible than Zapier.” — CEO at a small business, G2, Jan 2026
“I think the average user would not be able to figure these things out on their own. Having a more user friendly experience and better agent feedback would have saved me a lot of the initial challenges.” — G2 reviewer, Jan 2026
Standout feature: App Rules
App Rules turn an approval from a yes-or-no per tool into a condition on what the tool is about to do. The example in Gumloop’s own docs is the one most marketing teams want: send freely inside the company, ask a person the moment a recipient is outside it.
Verdict: a fit for a marketing-ops team that wants agents doing research and data work under rules as narrow as one recipient domain. Pass if finance needs next month’s bill before the month starts.
Pick the Builder for the Person Who Runs It
We build our own agents in code, so none of these seven runs ours. We needed these controls for our own agents, which is why we read the seven for them. The reply agent our team runs has each of them:
We keep the same separation on the Empact Panel, the weekly AI visibility report we build for partners. Their people accept or reject each recommendation, and every decision records who made it. Only we can add members.
Agent work with us starts inside RevOps, with the jobs your team does by hand every week. We pick one, agree on the number its agent should move before we build it, such as hours back or replies answered the same day, and a named consultant owns what the agent puts out. The builder gets picked last, for the people who will run it.
If your team is about to run its first agent, or has inherited one nobody dares switch on, put a call on my calendar, and we will see together whether building it is work for us.
