Follow-up that never forgets a lead.
Most deals die in the gap between touches. Here the gap does not exist: texts and emails go out the moment a call ends, written from the transcript of the conversation that just happened. No answer? The lead rides the loop and gets re-engaged on schedule until they respond. Every touch lands in one timeline you can read at a glance.
A live sequence
See a real follow-up thread: the call that started it, the texts that followed and the reply that booked the meeting.
The follow-up references what was actually discussed, because it was written from the transcript, not a template.
SMS for speed, email for depth, coordinated so the prospect never gets both at once or neither for weeks.
Unanswered leads are never marked dead. They cycle back on a schedule you set, until they answer or opt out.
Calls, texts, emails and notes stack in order on the contact. Anyone on your team can pick up any conversation.
From switched on to booked meeting.
A lead shows up
From your website, your lists or the In-Market add-on. The moment it lands, the clock starts.
The machine works it
Your agent calls in seconds, qualifies against your rules and follows up by text and email until someone answers. The coach watches every conversation.
Your calendar fills
Qualified prospects book themselves onto your calendar. The dashboard ties every meeting back to the call that earned it.
Six AI agents and sixteen tools, in place of fifteen subscriptions.
Businesses like yours pay for these separately, and none of them talk to each other. Here it is one system with one memory, so every call, text, email and booking knows what happened before it.
One platform. One memory. One bill.
Brand names belong to their owners.
- CRMHubSpot
- Phone systemRingCentral
- EmailMailchimp
- SMSPodium
- ReviewsTrustpilot
- SchedulerCalendly
- Chat and supportZendesk
- DM automationManyChat
- Social postingHootsuite
- ContractsDocuSign
- FunnelsClickFunnels
- Call trackingCallRail
- WebsiteSquarespace
- AutomationsZapier
- Call notesOtter.ai
Everything worth knowing, the long version.
19 chapters on how this actually works, written out in full.
Read the guideCommon questions
What Is AI Automation
AI automation uses artificial intelligence, including machine learning and natural language processing, to execute business tasks without manual direction. Unlike scripted software automation, it interprets context and handles exceptions. Lead qualification, follow-up, data entry and scheduling can all run continuously at scale.
What Is the Difference Between Traditional Automation and AI Automation
Traditional automation, including rule-based tools and RPA, executes a fixed script when a trigger fires. It is fast for predictable processes but breaks when conditions change. AI automation adds intelligence on top.
What Is Agentic AI
Agentic AI refers to systems that operate autonomously across multi-step tasks without a human defining each action. In a sales operation, it can monitor pipeline health, manage follow-up, book appointments and update CRM records simultaneously.
What Kinds of Tasks Can Be Automated with AI
AI automations handle tasks that are high-volume, repetitive or data-intensive: lead scoring, CRM data entry, follow-up sequences, appointment reminders, routine support responses, pipeline reporting and renewal triggers. Tasks requiring relationship intuition or executive judgment stay human.
Is AI Automation Expensive or Difficult to Implement
Cost depends on the scope of workflows and complexity of your systems. Most clients see positive ROI within 30 to 60 days from recovered rep time and better lead conversion, and most implementations go live within 10 to 21 days.
Does AI Automation Replace Human Workers
AI automation replaces repetitive tasks, not the humans who perform them. The average sales rep spends 64 percent of their workday on things other than selling. AI automations reclaim that time for building trust and closing deals.
What Are the Risks or Challenges of AI Automation
The primary risks are poor data quality, over-automation of processes that need human judgment, and weak governance. Bad input data produces bad outputs, and governance gaps mean you cannot account for an AI decision. Good implementations address all three upfront.
How Is AI Automation Different from Microsoft Copilot
Microsoft Copilot is a prompt-response assistant built into Microsoft 365: a human asks, it responds. Our AI automations operate autonomously at the workflow layer, running your business around the clock whether or not anyone is working.
What Does an AI Automation Agency Actually Do
An AI automation agency handles the full lifecycle rather than selling a tool and leaving the build to you: auditing workflows, designing the architecture and managing the system once live, all under one team.
Multiply Revenue