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AI AGENTS FOR BUSINESS

Custom AI Agents.
Built and Run for You.

The days of clicking, dragging, copying, pasting, deleting, downloading, and CTRL-F'ing are over. Assign your agent a job and it hands back completed work.

  • Wired into your existing tools.hubspot · gmail · slack · connected
  • Built around your process.lead_followup · step 3 of 4
  • Every action governed by your rules.2 drafts · awaiting approval

Founder-led Teams Use Machine-like Agents

The agent dilemma, solved.

THE THING ABOUT AGENTS NOBODY TOLD YOU

AI agents were supposed to free up time. In reality, they hand you a second job.

TWO BAD OPTIONS

And that's because most agents come in two varieties: the ones you have to build or the ones you have to babysit.

THAT'S WHERE WE COME IN

So we decided to fix it...

AN OLD SOLUTION TO A MODERN PROBLEM

With a Machine-like agent, we handle everything for you. From design, to deployment, to daily operations.

WE BECOME YOUR ACCOUNTABLE AGENT OPERATOR

We run your agents. You run your business.

AI AGENTS AS A SERVICE 🫡

We call it Managed Agent Operations.

FIG. 07 · MACHINE-LIKE TERMINAL

MLMachine-likeConsole
Search runs, receipts…⌘K

Workspace

  • Home
  • Inbox2
  • Agents4
  • Connections1 gap
Cyberdyne Systems29 Jul 2026 · 09:44:00LiveCustomerStaff

Operations overview

Agent workforce

Four agents under management. One run in flight, two decisions waiting on you.

Wednesday29 Jul 2026 · 09:44:00

2 approvals waiting on your decisionoldest 41 min · $18k pipeline exposedReview in Inbox →

Work completed · today

38▲ 12%

vs 34 daily average

Awaiting your decision

2of 41 today

95% cleared without you

Median first response

3m 12s

Inside 5-minute target

Hours returned · 7d

26.5▲ 4.1

≈ $1,340 of staff time

In flight

1 running · 1 queued
Lead ResponseDraft mode03:14 elapsed

Qualifying inbound lead: J. Moreno, Beacon Logistics

Qualification & Routing · step 3 of 8 · evaluating buying-readiness

Next: apply routing logic → identify owner

Step 6 will be skipped: no CRM connected

PauseOpen run →
Signup DigestDispatched, waiting to startqueued

Activity

Last 24h
  • 09:41Lead Response asked to send a reply to J. Moreno
  • 09:38New inbound lead captured from web form; routing started
  • 09:12Competitive Watch requested an action the console can't preview
  • 08:01Daily signup digest posted to #signups
  • TueCalendar booking failed for R. Patel; operations team notified, no action needed
  • TueReply approved and sent to D. Chen, Northgate

Agent roster

View all →
Lead ResponseInbound Lead Capture · 3 workflows · 24 steps
Working
Draft mode
7-day volume 87
Last activity 2 min ago
PauseOpen →
Signup DigestDaily signup reporting · 2 workflows
Idle
Autonomous + gates
7-day volume 7
Last activity Today 08:01
PauseOpen →
Competitive WatchMarket monitoring · 3 workflows
Needs you
Autonomous + gates
7-day volume 14
Last activity Today 09:12
PauseOpen →
Invoice ChaserAR follow-up · new work refused until re-enabled
Disabled
Disabled
7-day volume 0
Last activity Jul 12
Enable

[ MEET YOUR MACHINE-LIKE AGENT ]

Reclaim the work of humans.

Send your manual, tedious, mechanical tasks to an agent that keeps it moving. Machine-like agents are custom-built AI workers that autonomously handle entire workstreams, from the first step to the finished result.

Who it's for

Role

Owners, operators, or senior leaders at companies with 1–100 employees.

Work

Humans stuck doing manual, recurring, tedious, mechanical, machine-like tasks.

Stage

Curious about AI but not sure where to start, or already experimenting and ready to go further.

How it works

Agents do the work

Agents deliver fully completed work, well beyond answering questions in a chat.

We keep them running

Setup, monitoring, daily ops, maintenance, and upgrades are our job.

You're in control

You set the rules, approve key actions, and see everything that got done.

Agent runtime · Always on
Illustrative run

Finance recon

Reconciliation agentAutonomous + gates
Trigger
Nightly at 23:30, and when the bank feed updates
Reads
QuickBooks, Stripe payouts, bank feed
Does
Matches deposits and flags exceptions
Gate
Nothing posts to the ledger without your approval
Output
Exceptions report in Slack by morning
Connections
  • QuickBooks
  • Stripe
  • Bank feed
  • Slack
ReceiptRUN 0233
finance.reconcile_depositsStarted 23:30:00Surface · QuickBooks
  1. 23:30:00infoNightly run started
  2. 23:30:06info64 deposits read from the bank feed
  3. 23:31:18done61 matched to Stripe payouts and QuickBooks invoices
  4. 23:31:19gated3 exceptions: amount differs from invoice
  5. 23:31:40doneExceptions report posted to #finance
  6. 23:31:41gatedLedger entries held for your approval
GatedHolding 3 entries for approval
Elapsed00:01:41
After you log off · 18:00 → 08:002 runs · 1 completed · 1 gated

[ ONE ACCOUNTABLE AGENT OPERATOR ]

We run your agents. You run your business.

It's a simple exchange: human time for machine labor. Agents handle the taskers, to-dos, and the core operating work. You make the decisions and set the strategy.

We handle

  • Designing, configuring, and deploying your agent around the job you hand over
  • Monitoring, exception handling, and fixes, in week one and in month six
  • Maintenance, updates, and each capability upgrade as the work grows
  • Answering for the outcome: when a run fails, we catch it, and fix it

You own

  • The rules: what the agent does on its own, and what waits for your sign-off
  • Approvals: You decide what requires oversight or review
  • Verification: You get a work receipt for every completed task
  • The business: your customers, your pricing, your strategy
[ Managed Agent Operations ]

A new species of AI service.

Agents that are designed, deployed, and run for you. They integrate into your tech stack and are governed by your rules. No building or babysitting required.

Dimension/ Build it yourselfAgents that you buildA tool you construct/ Buy it and babysitAgents that you operateA tool you manageMachine-likeManaged Agent OperationsA partner that's accountable
Who builds the agents?You doVendorWe do, fully customized around your requirements
Who manages agents day-to-day?Your teamYour teamWe do, under your guidelines and policies
Who owns agent quality?You doVendorUs
How do agents receive tasks?You've built in custom triggers or cron jobsDefined by vendor configurationCustomized around your processes and workflows
Who fixes the agent when APIs break?You doYou doWe do
What do I pay before it worksBuild cost + value of your timeSubscription fee. Pay first, prove second.$0. Value gets proven first.
Where do I need to allocate resources?Agent design foundations, orchestration, guardrailsRunning agents in production and monitoring their performanceYou save resources. Our agents deliver completed work as a service.
How do I keep control?You've built in governance and permission gatesYour team is responsible for monitoringAgents are configured according to your guidelines and procedures. And then they get monitored by us.

Machine-like work should belong to machines.

What if your team could focus entirely on the human elements of business — relationships, judgment, ideas, creativity? Our agents take the mechanical, repetitive work slowing your team down and completes it at AI speed.

FIG. 08 · Prospecting run
Agentml-0919 · prospectingclaude-opus-4-8Gated

Run log8 steps

  1. 00:06apollo.search 142 ICP accounts
  2. 00:48apollo.enrich 87 contacts, 61% match
  3. 01:1212 CRM duplicates suppressed
  4. 02:05hubspot.sync 75 contacts synced
  5. 03:10draft.generate 75 drafts from briefs
  6. 03:31tone: direct, founder voice
  7. 04:09slack.notify #pipeline "75 ready"
  8. 04:12awaiting your approval to send
Connections4 / 4
SlackApolloHubSpotGmail
Enrich_contactsCompleted
matched
142 accounts
verified
87 contacts
Hubspot_syncCompleted
new
75 contacts
duplicates
12 suppressed
Draft_outboundGated
queued
75 drafts
review
awaiting you
workflow
prospecting
runtime
4m 12s
replaces
~4hr / week manual

[ Agents that can go where they're needed ]

Deploy across every job function.

Sales. Support. Operations. Marketing. Finance. Point your agent at any bottleneck where work tends to pile up.

Tour the Agent Factory

[ AGENTS THAT INTEGRATE WITH EVERYTHING ]

Full compatibility.

No rip and replace. Nothing migrates. Nothing gets rebuilt. Agents connect to the apps and software your business uses.

See latest integrations
FIG. 10 · Your stack, unchanged20 connected
Machine-likeMACHINE-LIKE
Comms
Slack
Gmail
Microsoft Teams
Notion Calendar
Zendesk
Work
Jira
Asana
Monday
Trello
GitHub
Files & data
Airtable
Box
OneDrive
Looker
Azure
CRM & people
HubSpot
Gong
Affinity
Greenhouse
Guru
MigrationNone
RebuildNone
Your toolsUnchanged
FIG. 10 · Connection map · A sample of supported tools

[ Designed for trust & safety ]

You're in control.

Agents reach only the systems you open. They stay in the lane you draw. When a decision requires judgment, they stop and wait for you.

GATERUN 0241
refund_request · order 88412 · $1,240.00Policy: refunds over $500 wait for a human
AWAITING YOU
11.A · Ledger
RUN 0182 · weekly_pipeline_report
  • 09:14:02READCRM · 142 deals
  • 09:14:31WRITESheet · 87 rows
  • 09:15:06SENTSlack · #revops
COMPLETED

Full transparency

Nothing happens off-camera. Every action is logged. Every completed task comes with a receipt.

11.B · Boundary
SCOPE · REVOPSAGENTCRM · READMAIL · DRAFTBILLINGOFF-LIMIT

Secure by design

Agent boundaries are written in code, not made in promises. Permissions, policies, and off-limit actions are enforced at the root.

11.C · Vault
  • In transitEncrypted
  • At restEncrypted
  • Run logEvery run
  • Model trainingNever
  • Data ownerYou

Data protection and privacy

Your data stays yours. Encrypted in transit and at rest, logged on every run, and never used to train a model.

FIG. 11 · Gate, ledger, boundary, vault
[ Agent anatomy 101 ]

Why use a Machine-like agent?

We build custom worker agents, not chat interfaces or personal assistants. Every agent runs on a harness: code that lets it act, see the result, and keep going. Inside are five things, a model, instructions, policies, tools, and memory, all configured around your specific job.

FIG. 09 · Agent anatomy · Core + 5 layers
Start for free
LAYER / 01

An identity with hard limits

Layer 1 is the identity file: who the agent is, its operating rules, the boundaries it never crosses. It rides along on every single turn. Model choice, runtime, and budgets are pinned in config. Nothing about the agent's behavior is improvised.

[ components ]05 parts
  1. 01.1AGENTS.md
  2. 01.2agent.config.ts
  3. 01.3Hard Boundaries
  4. 01.4Model & Runtime Config
  5. 01.5Cost Budgets
LAYER / 02

Capabilities that load on demand

Each task our agent can do is a self-contained skill: a documented procedure, deterministic scripts, and reference docs that load when needed. Tools are typed functions with schema-validated inputs. Specialist subagents take the deep work.

[ components ]06 parts
  1. 02.1SKILL.md
  2. 02.2Deterministic Scripts
  3. 02.3Typed Tools
  4. 02.4Triggers
  5. 02.5Schema-Validated Inputs
  6. 02.6Subagents
LAYER / 03

Permissions as code, not vibes

What the agent may do is written down, auditable, and enforced: which actions require a human and who that human is, when to stop and hand off, where the data and spend limits sit.

[ components ]06 parts
  1. 03.1Approval Gates
  2. 03.2Escalation Paths
  3. 03.3Data Boundaries
  4. 03.4Auth-Only Connections
  5. 03.5Spend Limits
  6. 03.6Off-Limits Actions
LAYER / 04

Memory that persists

No black box. State lives in durable, human-readable files: long-lived facts about the environment, the precedent behind every decision it has made, and the domain knowledge it consults but doesn't control.

[ components ]05 parts
  1. 04.1context.md
  2. 04.2decisions.md
  3. 04.3Knowledge Base
  4. 04.4Diffable State
  5. 04.5Domain Knowledge
LAYER / 05

Evals that drive improvement

Runbooks, drift checks, a dated changelog, and post-mortems keep everything verified in production. This is the layer almost nobody ships. We run on it.

[ components ]05 parts
  1. 05.1Regression Suite
  2. 05.2Scoring Rubrics
  3. 05.3Runbooks
  4. 05.4Drift Checks
  5. 05.5Changelog

Built for teams that execute

More case studies
01Espresso AI

“We looked at a few vendors, including building the agents ourselves. Every option required technical resources that we couldn't spare. I needed these tasks done, and the team at Machine-like just handled it.”

Portrait of Marthe NaudtsMarthe NaudtsHead of GrowthEspresso AI

Helping people, everywhere they work.

Sales, support, finance, HR. Our agents deploy anywhere across the org. Pick the task. Get back perfectly completed work.

CUSTOMER SUPPORT

Your queue will be clear by morning.

Agents take the first pass on every ticket. Your team handles the ones that actually require a human.

  • Drafts the first reply on every ticket
  • Routes the routine, escalates the rest
  • Runs inside your help desk, with your leaders on approval
Learn more
Finance

Never think about receivables again

Reconciliation, receivables, depreciation schedules, close support. The work that has to be right with too few people to do it.

  • Treasury & cash management
  • Financial planning & analysis
  • Tax planning
Learn more
MARKETING

Marketing that ships on schedule.

We turn your quarterly plan into published work and keeps everything on schedule.

  • Drafts content from your brief and brand voice
  • Schedules, publishes, and repurposes across your channels
  • Runs inside your marketing stack, with your leaders on approval
Learn more
SALES

No lead gets left behind.

Agents answer every new lead inside four minutes, qualifies it, books it, and hands your rep a warm opportunity.

  • Answers and qualifies every new lead in minutes
  • Routes, books, and follows-up (without needing a reminder)
  • Runs inside your CRM, with your leaders on approval
Learn more

[ REAL WORK. REAL RECEIPTS. THEN DECIDE. ]

Want to test a managed agent?

Start a 14-day free trial when your agent goes live. We configure the agent around your specific workflows, your preferred tools, and your exact procedures. Watch the agent deliver verified work. Then decide.

  1. start here01 / 03

    Try it for $0

    Create a free account and describe the work you'd like to automate. We'll custom build an agent that's designed specifically for your business.

    • Off-load an entire
    • Real work, not a sandbox
    • You control permissions and approvals
    • A receipt for every action
    • Proof, not promises
  2. trial launch02 / 03

    Your agent gets to work

    Deployment takes days, not quarters. Your agent runs your , follows your policies, and reports what it completed. You review and evaluate the results over 14 days.

    • Tailored to your process
    • Built around your business
    • Integrated across your systems
    • Zero building or babysitting required
    • We run and maintain your agent
  3. managed agent operations03 / 03

    Make the call

    Judge your agent by the work it delivers. To keep it on the job, choose a service plan. If it’s not a fit, walk away. All completed work is yours to keep.

    • Work delivered, week after week
    • Increased capacity without another hire
    • More time for customers and your team
    • Monitoring, maintenance, and upgrades included
    • One partner accountable for results

Don't see your question here? You can always ask us on a call →

What does Machine-like do?

Machine-like is the Managed Agent Operations company. We design, deploy, and run custom AI agents for small businesses, as a service. Machine-like agents work inside the software you already use and hand back finished work: sales follow-up, support triage, reporting, reconciliation, and more. You tell us the job. We build the agent, run it in production, and stay accountable for the results.

What is Managed Agent Operations?

Managed Agent Operations is a service model where AI agents are designed, deployed, and run for you. Today most agents come one of two ways: you build them yourself, or you buy them and babysit them. Both leave your team operating software. Managed Agent Operations is the third option. We build the agent around your process, connect it to your tools, monitor it, fix it, and upgrade it. You keep the approvals and the judgment calls.

What kind of work can Machine-like agents do?

Machine-like agents handle defined, repeatable work across sales, support, operations, marketing, and finance. Common jobs include answering and qualifying new leads in minutes, booking and follow-up, prospect research, support ticket triage, customer intake and onboarding, CRM hygiene, recurring reporting, and deposit reconciliation. Each agent owns a specific job with a clear trigger and a finished output, which is what keeps it reliable. If a task repeats every week and runs through software, it is a strong candidate. Open-ended chat assistance is not what we build.

Is this a fit for a business like ours?

Machine-like agents are built for owners, operators, and senior leaders at companies with roughly 1 to 100 employees. The best fit is a business with real, recurring workflows (customers, vendors, pipelines, reports) and a small team carrying too much of it by hand. You do not need an AI strategy first. Whether you are curious about AI and unsure where to start, or already experimenting and ready to go further, we help you pick the right first job.

How are Machine-like agents different from other AI agents?

Most AI agents arrive as software you have to operate. Build one on a platform and your team designs, tests, and maintains it. Buy one off the shelf and your team monitors and babysits it. Tools that generate agents for you still leave you running them: self-creating is not self-managing. Machine-like agents are built, run, and maintained by us, customized around your process and governed by your rules. You get completed work, not a second job.

How does the free trial work?

Create a free account and join a short scoping call so we learn your tools, your rules, and what done looks like. Your 14-day free trial starts when the agent goes live on real work, not when you sign up. No credit card, no setup fees, no obligation. If the agent proves itself, roll into a service tier. If it doesn't, you walk away and owe nothing.

How much of our time will this take, and do we need technical people?

Very little, and no. We do the heavy lifting: scoping, building, integrating, testing, and running the agent. Your part is short and front-loaded: access to the right tools, the rules your team follows, examples of work done well, and one person who can make approval decisions. After launch, you review what the agent hands back. You will not troubleshoot APIs or babysit live runs.

Will the agent act without our approval?

Only where you allow it. Every Machine-like agent starts in draft-and-approval mode, so nothing goes out without your sign-off. You set the rules: what the agent may do on its own, which actions wait for a human, and what is off-limits entirely. When a decision calls for judgment, the agent stops and waits for you. Every completed task comes with a receipt, so you verify the work instead of trusting claims.

What happens when something breaks or an API changes?

We fix it. When an integration changes, a connection expires, or an agent drifts in month six, catching and repairing it is our job, not yours. We monitor every agent in production, keep it current as your process evolves, and handle model upgrades. That is the difference between a managed service and a tool you have to operate.

Is our data, and our customers' data, secure?

Yes. Your data stays where it lives. Nothing migrates out of your CRM, inbox, or other tools. Agents reach only the systems you authorize, through connections you control and can revoke at any time, and they take only the actions their workflow calls for. Data is encrypted in transit and at rest, every run is logged, and your data is never used to train AI models, ours or anyone else's. You own your data.

How much does it cost?

Pricing is per workload, billed monthly. A workload is the complete job an agent owns, sized to replace roughly 5 to 10 hours of manual work each week. Operator covers 1 to 2 workloads at $249 per workload per month. Growth covers 3 to 5 workloads at $199 per workload per month. Command covers 6 or more workloads with a custom quote. Every tier includes unlimited seats and connectors, with no setup, integration, or platform fees. Cancel anytime.

Make time forthe work of humans⁠1

Give your people more space for ideas, relationships, and creativity.