The Short Answer
Machine-like fits a founder-led or operator-led business with recurring digital work piling up that wants it handled by an accountable operator. Your team sets the rules and keeps the decisions. We build the agent, run it on your existing tools, and repair it when the workflow or an integration changes.
| Decision field | What to know |
|---|---|
| What you buy | A complete stream of recurring work, built and operated for you. |
| Best for | Lead response, support triage, operations, finance, marketing, reporting, and AI visibility. |
| Your team keeps | Operating rules, approval decisions, relationships, and judgment. |
| Machine-like owns | Build, integrations, testing, monitoring, maintenance, and repair. |
| Human control | New agents start in draft-and-approval mode. Autonomy follows testing and your sign-off. |
| Current plans | Operator: $249 /mo per workload (1-2 workloads); Growth: $199 /mo per workload (3-5 workloads); Command: Custom quote (6+ workloads) |
Fit Check
Score one workload you have in mind. Pick the single stream of work you would hand off first and count the statements that are true for it.
This is an advisory self-assessment, not an eligibility rule or a measured predictor of results. Use the score to choose the next conversation; your workload still needs to be scoped.
Score / 8
Scoring Rule
Give yourself one point for each true statement, for a total from 0 to 8. Check the disqualifiers before using the suggested verdict bands.
Verdict Bands
Start a trial conversation around this workload.
Start with the narrowest useful version and discuss what needs to change.
Clarify the process or consider a narrower tool before taking on a managed service.
Hard Disqualifiers
The managed model is a poor fit regardless of score if any of these is true:
- You want to build and operate agents yourself.
- You only need a standalone chatbot, a meeting transcriber, or a general writing assistant.
- You are pre-revenue with limited runway and no repeatable motion to amplify.
- You need a global transformation vendor with enterprise procurement support.
What One Workload Looks Like
A workflow is one repeatable process: a defined trigger, a sequence of tasks, and a finished output you can inspect. Sending a weekly pipeline report is a workflow.
A workload is bigger. It is the complete stream of work a Machine-like agent owns end to end, bundling every workflow that stream needs. Inbound lead handling is a workload: every inbound lead answered, enriched, routed, followed up until it books, logged, and reported.
A workload is the job you hire an agent to do.
Workflows are never priced or sold alone. The big ones do the visible work, the small ones like reporting and CRM hygiene come included, and our engineers configure and tune all of them as part of the service. No meters, no seats, and no math about which workflow ran how many times.
Worked Example: Inbound Lead Handling
Trigger: A new lead arrives by web form, inbox, or chat.
Finished output: The lead is answered, enriched, qualified, routed, followed up, logged, and reported according to your rules. Your team approves the actions you keep gated.
Workflows Inside This Workload
- Reply to the lead.
- Enrich the contact and company.
- Qualify against your rules.
- Route to the account owner.
- Offer a meeting and follow up until the lead books or the opportunity closes.
- Log activity and maintain the CRM record.
- Prepare the pipeline report.
Illustrative Work Receipt
Illustrative receipt. Names and content are invented.
| Field | Example |
|---|---|
| Input | Form submission from Dana, an operations lead asking for help with dispatch follow-ups. |
| Steps | Enrich the contact; apply your qualification rules; identify the account owner; draft a reply; prepare the CRM update. |
| Sources | Approved qualification rules, the current FAQ, and the territory map. |
| Output | A draft reply, a CRM update, and proposed meeting times. |
| Approval | Awaiting the sales lead's approval before a customer-facing message is sent. |
One Workload or Two?
Count complete streams of work, rather than every small workflow inside them. Scope the boundaries with us before choosing a plan.
| The work | How to think about the scope |
|---|---|
| Inbound lead handling, including its pipeline report | One stream of work. Reporting belongs inside the lead-handling workload. |
| CRM cleanup and activity logging for those leads | Workflows inside that workload, rather than separate products. |
| Support ticket triage and approved replies for the same queue | Discuss as one support stream with a shared trigger and finished output. |
| Support triage and overdue-invoice follow-up | Two distinct streams to scope: support and receivables. |
| Inbound lead handling and outbound prospecting | Two distinct streams to scope: inbound response and outbound prospecting. |
How the Free Trial Runs
Do you pay during configuration or the trial? No. The 14-day free trial costs nothing. You create an account, connect where your work lives, and kick off configuration the same day. Our engineers tune the agent to your processes, your tools, and your approval rules, and the trial clock starts only once your agent goes live on real work.
- Setupcreate an account and connect your tools. Connect the systems where the work lives with credentials you can revoke.
- Configureour engineers fit the agent to your process. Your tools, rules, and approval gates define the work. Configuration happens before the trial clock starts.
- Go livethe trial clock starts on real work. The agent begins in draft-and-approval mode, and completed tasks leave receipts you can inspect.
- Reviewtune the workload and inspect the results. Routine actions can gain autonomy after the workflow proves reliable and you approve the change.
- Decideevaluate the completed work. Continue into a plan or walk away. You walk. No subscription, no invoice for the setup, no "but you owe us" conversation. We carry the full cost of the trial because we are confident the agent will prove itself.
What Your Team Provides
The tools involved, examples of the work done today, the rules your team follows, approved source material, and one internal owner who can make approval decisions.
Pricing
Operator
1-2 workloads
$249 /mo per workload
5 - 20 hrs / week saved
- Unlimited seats
- Custom skills and APIs
- Unlimited connectors
- Email + Slack support
Growth
3-5 workloads
$199 /mo per workload
15 - 50 hrs / week saved
- Unlimited seats
- Custom skills and APIs
- Unlimited connectors
- Email + Slack + Video support
Command
6+ workloads
Custom quote
50+ hrs / week saved
- Unlimited seats
- Custom skills and APIs
- Unlimited connectors
- Dedicated Customer Success Manager
The math on one workload
$249 /mo per workload
What one workload replaces:
- 5–10 hrs/week of manual tasks
- $1,500–$3,000/mo of paid time
Compared With the Alternatives
There are three common ways to get agents: build them, buy an agent product and operate it, or hire an operator. Choose based on who should own the work after launch.
| Responsibility | Build it yourself | Buy it and operate it | Hire Machine-like |
|---|---|---|---|
| Build and integrations | Your team | Your team or a partner | Machine-like |
| Run it in production | Your team | Your team | Machine-like, with your team on approvals |
| Monitor quality and exceptions | Your team | Your team | Machine-like |
| Repair drift and API changes | Your team | Your team | Machine-like |
| Business judgment | Your team | Your team | Your team |
By Name
| Alternative | Choose it when | Choose Machine-like when |
|---|---|---|
| Lindy | You want an AI teammate you set up and direct yourself. | A complete stream of work needs an accountable operator in production. |
| Zapier Agents, Make, Gumloop, or n8n | You have a hands-on automation owner who wants construction control. | Nobody on the team should carry agent building, monitoring, and repair. |
| Intercom Fin | Support is the whole problem and your team owns the surrounding helpdesk, knowledge base, and policies. | Support crosses into CRM, billing, or product systems, or the operator should handle other functions too. |
| HubSpot Customer Agent or Zendesk AI agents | You want AI inside the platform that is already your source of truth. | Work crosses product boundaries or your team has no named agent owner. |
| Salesforce Agentforce or Microsoft Dynamics 365 agents | You are building an internal agent program around an enterprise suite. | You are founder-led and want a working agent operated on your existing tools. |
| ChatGPT or Claude | You want help thinking, writing, researching, or coding. | You need recurring work completed inside business systems under rules and approvals. |
| An automation agency | You want a project build and can own continuing operation. | You want production monitoring, maintenance, and repair included in the service. |
| Hiring someone | The role needs relationships, negotiation, physical presence, or broad judgment. | The work is recurring, digital, and follows rules you can explain. |
Works With the Tools You Already Run
Will it work with the tools we already use? Yes. We build on the tools you already own. Standard integrations cover the common revenue, communication, and operations platforms (HubSpot, Gmail, Slack, Calendar, Notion, Salesforce, Apollo, Linear, Stripe, Intercom, Airtable, and the usual suspects). Advanced integrations covering deeper API work, custom middleware, or legacy systems are scoped. No rip and replace, no forced migration.
Standard Integrations
- HubSpot
- Salesforce
- Gmail
- Calendar
- Slack
- Notion
- Apollo
- Linear
- Stripe
- Intercom
- Airtable
Proof, by Function
The results below distinguish agents running business operations from AI-search visibility. They describe the linked engagements, rather than a guarantee for your workload.
Agent Operations: Support
82%
of Tier 1 tickets automated at fitDEGREE. The support engagement also reduced average first-response time by 68% and ticket backlog by 54%.
Agent Operations: Marketing Analytics
Always-on QA
A performance marketing analytics team used agents for data readiness, request triage, first-pass analysis, monitoring, and reporting. Decision Scientists kept experiment design, interpretation, governance, and final recommendations.
AI Visibility: Travel
47%
citation share in three weeks for Lake. Lake became the category leader in the measured AI-search results, ahead of larger travel brands.
AI Visibility: Education
2x
signups at CourseCareers. The AI-visibility engagement also produced a 112% increase in AI-driven traffic.
Security and Control
Your Systems Stay Put
Agents reach your tools through credentials you control and can revoke. Access is scoped to the authorized job.
Your Data Is Not Used for Training
Machine-like states that client data is not used to train AI models. You own your data and outputs.
Autonomy Follows Your Approval
Draft-and-approval is the starting posture. Judgment calls and out-of-policy work go to an exception queue or a human. You grant autonomy after the workflow proves reliable.
Work Is Logged and Maintained
Machine-like states that data is encrypted in transit and at rest and that every run is logged. Production agents include regression testing, drift checks, runbooks, and a dated change history.
Common Questions
Is Machine-like just ChatGPT connected to our software?
No. A chat interface does not by itself define permissions, retrieve operating context, execute multi-step work, handle exceptions, evaluate quality, log actions, or repair integrations. Machine-like combines models, retrieval, orchestration, approvals, monitoring, and human operation into a production system.
Do we need technical people?
No. Machine-like handles requirements, build, integrations, testing, deployment, monitoring, and maintenance. You provide access, operating rules, approved source material, examples of the work, and a person who decides on exceptions.
Can the agent act without approval?
New agents start in draft-and-approval mode. Routine actions can gain autonomy after the workflow proves reliable and you explicitly approve the change. Sensitive, financial, customer-facing, and brand-sensitive actions can remain gated.
What happens when a credential breaks or an API changes?
Machine-like diagnoses and repairs it. Continuing responsibility for drift, broken credentials, changed APIs, and degraded output is part of the managed service.
What does per workload mean?
A workflow is one repeatable process: a defined trigger, a sequence of tasks, and a finished output you can inspect. Sending a weekly pipeline report is a workflow.
A workload is bigger. It is the complete stream of work a Machine-like agent owns end to end, bundling every workflow that stream needs. Inbound lead handling is a workload: every inbound lead answered, enriched, routed, followed up until it books, logged, and reported.
A workload is the job you hire an agent to do.
Workflows are never priced or sold alone. The big ones do the visible work, the small ones like reporting and CRM hygiene come included, and our engineers configure and tune all of them as part of the service. No meters, no seats, and no math about which workflow ran how many times.
Do I pay anything before I see the agent working in my environment?
No. The 14-day free trial costs nothing. You create an account, connect where your work lives, and kick off configuration the same day. Our engineers tune the agent to your processes, your tools, and your approval rules, and the trial clock starts only once your agent goes live on real work.
What if the trial does not prove the workload?
You walk. No subscription, no invoice for the setup, no "but you owe us" conversation. We carry the full cost of the trial because we are confident the agent will prove itself.
Are there setup fees or a long-term commitment?
No setup, integration, or platform fees, ever. Yes. You are free to cancel at any time, for any reason.
What happens if we cancel?
Yes. You are free to cancel at any time, for any reason.
Will our data be used to train models?
No. Machine-like states that client data is not used to train AI models. You own your data and outputs. Access to your systems is scoped and revocable.
Will this replace an employee?
Agents absorb repeatable digital work. People keep relationships, negotiation, judgment, and approvals. Machine-like measures the workload completed, rather than promising to eliminate a role.
Who is behind Machine-like?
Machine-like is a New York company founded by Kurt Fischman. Meet the company and founder.
The Bottom Line
Machine-like is worth evaluating when you need recurring digital work completed and want an operator responsible for running it.
- Choose the workload.
- We build and prove the agent on your real work.
- Your people keep approvals and judgment.
- We stay accountable for running and repairing it.