AI agents & automation
AI agents for marketing, sales and analytics teams
Agents that take repetitive, multi-step work off your team, connected to the tools you already use, with a person approving what matters.
- TriggerNew demo request from the website form
- ContextCompany size, industry and past visits added from the CRM
- PlanFit score 82 of 100. Matches two ideal-customer rules
- ToolsRecord updated and routed to the West region owner
- CheckFollow-up email drafted and waiting for approval
What it is
An AI agent is software that works toward a goal: it notices a trigger, gathers context, decides the next step and uses your tools to act, then logs what it did. ATL Martech designs, builds and supports agents for marketing operations, analytics, content and sales, starting with one measured pilot.
Who it’s for
- Marketing and sales teams buried in QA, reporting, routing and follow-up
- Leaders who want a measured AI result, not another tool subscription
- Agencies that need a white-label partner to build agents for their clients
How an agent works
Six parts, and a person in the loop.
Every agent we build has the same structure, so you always know what it can see, what it can do and who signs off.
- 01TriggerA form fill, a schedule, a new record or a message
- 02ContextOnly the data and documents its job needs
- 03PlanThe next step, within rules you set
- 04ToolsYour CRM, analytics, CMS, email and chat
- 05CheckA person signs off on anything that matters
- 06Act & logEvery step saved so it can be reviewed
Guardrails around every step
The problem
What we’re usually called in to fix.
Busywork crowds out real work
Skilled people spend hours checking links, cleaning records and copying numbers between tools.
Pilots that never ship
Experiments stall because nobody connected them to real systems, data and approvals.
Risk nobody has scoped
Unclear rules on what an AI tool can see, change or send on your behalf.
Agent, assistant or automation?
Use the simplest thing that works.
Not every job needs an agent. Here’s how we decide, and we’ll tell you when a simpler tool will do.
| Rules-based automation | AI assistant | AI agent | |
|---|---|---|---|
| What it is | Fixed if-this-then-that steps | A chat tool that answers when asked | A system that works toward a goal, deciding its next step and using your tools |
| Best for | Predictable, repetitive tasks | Drafting and questions, one at a time | Multi-step work that needs judgment across several systems |
| Examples | Copy a form entry to the CRM | Draft an email when prompted | Qualify a lead, enrich it, route it and draft the follow-up |
| Handles exceptions | No, it stops or errors | Only if a person spots them | Yes, within rules you set, and escalates the rest |
| Human role | Maintains the rules | Asks every time | Approves key actions and reviews the log |
When an agent is the wrong answer
- The steps never change. A fixed automation in your CRM or Zapier is cheaper, faster and easier to maintain.
- The data isn't there yet. If the agent can't reach clean, current data, fix the data first. We'll say so.
- One mistake is unaffordable. Legal, medical or financial decisions stay with people. An agent can prepare the file, not make the call.
- It happens twice a year. The build and upkeep won't pay back. A checklist or a template will.
Example agents
What an agent could do for your team.
Six of the agents we can build, one from each area. Each card shows what starts it, what it connects to, what a person approves and how it’s measured.
-
Marketing operations
Campaign QA agent
Checks every email and landing page before launch: links, UTM tags, tracking, images, legal footer and brand rules. Posts a pass or fail report with fixes.
- Starts when
- A campaign is marked ready for review
- Works with
- HubSpot or Salesforce Marketing Cloud, GA4, Slack
- You approve
- The campaign owner approves the send
- Measured by
- Errors caught before launch; QA hours saved
-
Analytics & reporting
Weekly performance narrator
Pulls the week's numbers from analytics, ad platforms and the CRM, explains what moved and why, and drafts the leadership summary.
- Starts when
- Every Monday morning
- Works with
- GA4, Ad platforms, CRM, Looker Studio
- You approve
- An analyst checks the story before it's sent
- Measured by
- Reporting hours saved; questions answered in the report
-
Content, SEO & AI search
Content refresh agent
Finds pages losing search traffic, works out why, and drafts updates: new sections, fresher facts, better titles and internal links.
- Starts when
- Monthly Search Console review
- Works with
- Google Search Console, Your CMS
- You approve
- An editor approves changes before publishing
- Measured by
- Traffic recovered on refreshed pages
-
Sales & CRM
Inbound lead qualifier
Reads each form submission, adds public company details, scores fit against your ideal customer, and routes it to the right person with a summary.
- Starts when
- A new form submission or demo request
- Works with
- HubSpot or Salesforce, Your website forms, Slack
- You approve
- Sales confirms fit before outreach
- Measured by
- Speed to first response; qualified-lead rate
-
Customer experience
Support triage agent
Classifies incoming emails and tickets, drafts replies from the knowledge base, and escalates urgent or sensitive issues right away.
- Starts when
- A new ticket or email arrives
- Works with
- Help desk, Knowledge base, Email
- You approve
- An agent reviews drafts before they're sent
- Measured by
- First-response time; correct routing
-
Operations & knowledge
MarTech spend monitor
Tracks licenses, seats and usage across your marketing tools and flags unused seats and overlapping tools before renewal dates.
- Starts when
- Monthly, and 60 days before each renewal
- Works with
- Vendor admin consoles, Finance exports
- You approve
- The budget owner decides
- Measured by
- Spend removed at renewal
These are examples of what we design and build, not client case studies.
Packages
Four ways to work with us, in order.
Start with the workshop, prove one agent, then scale and support what works. You can stop after any step, and each one has a fixed scope.
-
01Start here
Agent Opportunity Workshop
1 to 2 weeks
Teams that know AI could help but not where to start.
- Workflow walkthroughs with the people who do the work
- Opportunity scorecard: value, feasibility, risk and data readiness
- Pilot specification: goal, trigger, tools, guardrails, success measures
- Data and access checklist for IT and legal
- Baseline of time and cost today, so results can be measured
You leave with: A short list of agents worth building, and a spec for the first one.
Request a workshop -
02Prove it
Agent Pilot
4 to 6 weeks
One high-value workflow you want working, with real data and real users.
- One agent built and connected to your systems
- Test set of real examples, with results before launch
- Guardrails: least-privilege access, approval steps, action log
- Launch with a small group, then tune from their feedback
- Run book and a before-and-after results readout
You leave with: One agent running in your stack, with measured results against the baseline.
Plan a pilot -
03Scale it
Agent Build & Integrate
6 to 12 weeks
Teams ready to run several agents, or one workflow across several systems.
- Multiple agents or a multi-step workflow across systems
- Integration with CRM, marketing automation, analytics and chat tools
- Monitoring, alerting and an audit trail for every action
- Access controls reviewed with IT and security
- Team training and handover documentation
You leave with: Production agents integrated with your CRM, marketing and data platforms, monitored and documented.
Scope a build -
04Keep it working
AgentOps
Monthly
Agents in production that need to stay accurate as your business, data and models change.
- Monitoring, error review and fixes
- Monthly re-run of the test set after any model or prompt change
- New skills and small workflow changes
- Model and cost reviews as platforms change
- Monthly report: usage, accuracy, time saved, open issues
You leave with: Agents that stay reliable, with a monthly report on accuracy, usage and time saved.
Ask about AgentOps
Timelines are typical. Pricing is fixed per engagement and agreed in writing before work starts.
Guardrails
Built to be trusted, and checked.
An agent is only useful if your team, IT and legal are comfortable letting it work. These come with every agent we build.
Least-privilege access
Each agent gets only the systems and permissions its job needs, with its own credentials.
People approve what matters
Anything customer-facing, anything that spends money and anything irreversible waits for a person.
Tested before launch
Every agent runs against a set of real examples, and we re-run it after every change.
A log of every action
What the agent saw, decided and did, so you can review it and explain it.
An off switch
Any agent can be paused instantly without breaking the systems around it.
Your data stays yours
Business-grade AI platforms with data-protection terms, built in your accounts, documented for legal and IT.
How the work runs
Map, pilot, integrate, operate.
The same people plan the agent, build it and support it, so nothing gets lost in a handover.
- 01
Map
Walk through the workflows with the people who do them, and score each one.
- 02
Pilot
Build one agent with real data, tested against real examples.
- 03
Integrate
Connect more systems and agents once the first one proves its value.
- 04
Operate
Monitor, re-test and improve as your data, tools and models change.
Platforms we build with
- OpenAI
- Anthropic Claude
- Google Gemini
- Microsoft Copilot Studio
- Salesforce Agentforce
- HubSpot Breeze
- n8n
- Make
- Zapier
- Google BigQuery
- Slack
- Microsoft Teams
We’re independent and take no referral fees, so we choose the platform that fits your stack, your data rules and your budget. Often that’s AI already built into tools you pay for.
What is an AI agent?
An AI agent is software that works toward a goal on its own: it reads what's happening, decides the next step, uses tools such as your CRM or analytics, and checks its own progress. Unlike a chatbot, it doesn't wait to be asked each time. Unlike a fixed automation, it can handle cases that don't follow the script.
Do we need an agent, or would a simple automation do?
Often a simple automation is enough, and we'll tell you. Agents earn their cost when a task needs judgment, spans several systems or has many exceptions. The Agent Opportunity Workshop sorts your workflows into both groups.
Will an agent make mistakes?
Sometimes, which is why every agent we build is tested against real examples before launch, limited to the access it needs, and set up so a person approves anything customer-facing, costly or irreversible. Every action is logged.
How much does it cost?
It depends on the number of agents, systems and approval steps. The workshop is a fixed-scope engagement, and after it you get a fixed-price proposal for the pilot, based on the specification we write together.
Who owns the agent?
You do. We build in your accounts wherever possible and hand over the configuration, prompts, test sets and documentation, so you're not locked in to us.
Can you build agents for our agency's clients?
Yes. We work white-label as a subcontractor, under your brand and your process, and the agents are built in your client's accounts.
Next step
Find the agent worth building first.
Start with an Agent Opportunity Workshop. We’ll walk through your workflows, score them, and write the specification for a first pilot you can measure.
Prefer email? contact@atlmartech.com