Majstori Grada Case Study: 24/7 AI Lead Machine
How Majstori Grada deployed four AI agents — lead capture, after-hours call center, sales knowledge, and QA — into one system that captures leads 24/7 and scores every call for BANT compliance.
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What was built: Majstori Grada deployed four specialized AI agents on the Growww AI Engine — a website lead chat, an after-hours AI call center, a knowledge agent for the sales team, and a QA agent that monitors every call for script and BANT compliance. The four agents operate as one coordinated system, capturing leads 24/7, covering the hours no human team can staff, and scoring every sales interaction automatically. Read the full case study here.
The Problem: Leads Don't Arrive on a Schedule
Majstori Grada is a home services business. Like every service business, their leads arrive when customers have a problem — and problems do not respect business hours. A pipe bursts at 11 PM. A heating system fails on a Sunday morning. A customer Googles "emergency repair" at 6 AM before the office opens.
The traditional answer is an after-hours call center or an answering service. Both are expensive, inconsistent, and limited. Answering services take messages but cannot qualify leads, book appointments, or answer questions about services. Human after-hours teams are costly to staff and difficult to scale. The result is the same in every service business: leads arrive around the clock, but the business only captures them between 9 and 5.
The gap between when leads arrive and when the business can respond is where revenue leaks. Every missed lead between 22:00 and 07:00 is a customer who calls the next business on the Google results page.
The Solution: Four Agents, One System
Majstori Grada deployed four specialized AI agents on the Growww AI Engine, each built for one job, coordinated as a single system.
The first agent is a website chat that captures urgent leads with minimal friction. When a customer lands on the website — at any hour — the chat agent engages, qualifies the request, captures contact information, and determines whether the lead needs immediate follow-up.
The design principle is friction reduction. Every additional field, every additional step, every additional question is a point where the customer can abandon. The lead chat is built to capture the essential information — who, what, where, how urgent — and get out of the way. The lead is then routed to the next agent in the system based on urgency and time of day.
The second agent is an AI voice call center that covers the hours no human team can staff: 22:00 to 07:00. When a lead comes in during after-hours — whether from the website chat, an inbound call, or a voicemail — the voice agent handles the conversation.
The voice agent does what an answering service cannot: it qualifies the lead, answers questions about services, books appointments, and logs the full conversation. It handles inbound calls with IVR and intent routing, and it can make outbound calls for reminders and follow-ups. Voicemail detection ensures the agent does not waste time leaving messages on machines — it logs the attempt and moves to the next lead.
The after-hours coverage is the highest-ROI piece of the system. Every lead captured between 22:00 and 07:00 is a lead that would have been lost to a competitor. The marginal cost of an AI agent handling that call is near zero. The marginal revenue is the full value of the captured lead.
The third agent is an internal knowledge agent that supports the human sales team. When a sales rep is on a call and needs information — pricing, service availability, scheduling windows, technical specifications — the knowledge agent retrieves it instantly from the company's knowledge base.
This agent does not interact with customers. It interacts with the sales team, making them faster and more accurate. Instead of putting a customer on hold to look up information, the rep asks the knowledge agent and gets the answer in real time. The result is shorter calls, fewer mistakes, and a more professional customer experience.
The knowledge agent is role-aware and auditable. It logs every query, every retrieval, and every response. The sales manager can see what information the team is asking for most frequently — which reveals gaps in training, documentation, or pricing clarity.
The fourth agent is the one most businesses never think to deploy — and it is the one that drives the most measurable revenue lift. The QA agent monitors every sales call for script compliance and BANT qualification.
BANT is a sales qualification framework: Budget, Authority, Need, and Timeline. Every sales call should assess these four factors. In practice, human sales reps skip them, rush them, or forget them under pressure. Human QA teams can sample maybe 2% of calls. The QA agent covers 100%.
The QA agent analyzes every call — whether handled by a human or by the after-hours voice agent — and scores it against the approved script and BANT criteria. It flags calls where the rep missed a qualification question, deviated from the script, or failed to capture a key piece of information. The sales manager receives a daily report showing exactly where the sales process is breaking down.
This is the agent that turns the system from a lead-capture tool into a revenue optimization system. Capturing leads 24/7 is valuable. Ensuring every lead is qualified correctly and every call follows the process is what converts those leads into revenue.
How the Four Agents Work as One System
The four agents do not operate in isolation. They are coordinated by the Growww AI Engine's orchestration layer, which routes tasks, maintains state across interactions, and ensures the customer experience is continuous.
A customer who starts on the website chat at 11 PM, gets a follow-up call from the after-hours voice agent, and then is handed to a human sales rep in the morning experiences a single, continuous interaction — not four disconnected conversations. The human rep sees the full casefile: the chat transcript, the voice call recording, the CRM record, and the QA analysis. The customer never repeats themselves.
This is what agent orchestration makes possible. Four specialized agents, each excellent at one job, coordinated as one system, governed by audit trails and QA scoring. No single agent could do all of this. No chatbot could do any of this.
What This Deployment Proves
The Majstori Grada deployment proves three things that matter to any service business evaluating agentic AI.
First, after-hours coverage is the fastest path to ROI. The leads that arrive between 22:00 and 07:00 are the leads the business was previously losing. An AI voice agent captures them at nearzero marginal cost. The payback period on this alone is measured in weeks, not months.
Second, QA is the hidden revenue lever. Most businesses focus on lead capture and ignore call quality. The QA agent reveals that a significant percentage of captured leads are lost not because the lead was bad, but because the sales process was not followed. Fixing the process — which the QA agent's daily reports make visible — is the fastest way to increase close rate without increasing lead volume.
Third, a multi-agent system outperforms any single agent. The lead chat, the voice agent, the knowledge agent, and the QA agent each do one thing excellently. Trying to combine them into one agent would degrade quality on all four tasks. Specialization plus orchestration is the architecture that scales.
The Architecture Behind the Deployment
The Majstori Grada system runs on the Growww AI Engine with the following architecture:
- Deployment: On the client's infrastructure, ensuring data control and GDPR compliance
- Voice engine: Inbound and outbound, IVR with intent routing, voicemail detection, warm transfers, call recording and transcripts
- Chat widget: Embeddable on web and mobile, conversational forms, lead capture with qualification
- Knowledge agent: Connected to the company knowledge base, role-aware, auditable
- QA agent: Call analysis for script compliance and BANT scoring, daily management reports
- CRM integration: All agents write to and read from the CRM, ensuring a single source of truth
- Orchestration: The Growww AI Engine routes tasks across agents and maintains state across channels
This is not a chatbot. It is not an answering service. It is a coordinated agent fleet that captures leads 24/7, supports the sales team in real time, and scores every interaction for compliance and quality.
Could This Work for Your Business?
The Majstori Grada deployment is not unique to home services. The same four-agent architecture applies to any business that captures leads, schedules appointments, and has a sales team that could benefit from real-time knowledge support and automated QA scoring.
Healthcare providers can deploy the same system for patient lead capture and after-hours coverage. Professional services can use it for consultation booking and intake. Any business with a sales floor and after-hours lead flow can replicate this architecture.
The question is not whether your business needs a 24/7 lead machine. If you receive leads outside business hours — and you do — the question is whether you are capturing them or losing them to the next listing on Google.
Read the full Majstori Grada case study to see the deployment in detail.
FAQ
An AI lead machine is a multi-agent system that captures, qualifies, and follows up with leads 24/7 across channels — website chat, voice calls, and CRM workflows. Unlike a single chatbot, it uses multiple specialized agents (lead capture, voice, knowledge, QA) coordinated by an orchestration layer. The Majstori Grada deployment is a real-world example: four agents operating as one system, capturing leads around the clock and scoring every call for BANT compliance.
An after-hours AI call center uses a voice agent to handle inbound and outbound calls during hours when no human team is staffed — typically 22:00 to 07:00. The voice agent answers calls with IVR and intent routing, qualifies leads, books appointments, detects voicemail, and logs full transcripts. Every lead captured during after-hours is a lead that would otherwise be lost to a competitor. The marginal cost per call is near zero.
BANT is a sales qualification framework that assesses Budget, Authority, Need, and Timeline. A QA agent monitors every sales call — whether handled by a human or an AI voice agent — and scores it against BANT criteria and the approved sales script. It flags calls where qualification questions were missed or the script was not followed. Human QA teams sample 2% of calls; an AI QA agent covers 100%.
Yes. A multi-agent AI system with a website chat agent and an after-hours voice agent captures leads around the clock. The chat agent handles web visitors at any hour, and the voice agent handles calls during unstaffed hours. Both agents qualify leads, book appointments, and log full transcripts to the CRM. Leads are not just captured — they are qualified and routed for follow-up before the human team arrives in the morning.
The Growww AI Engine uses an orchestration layer that routes tasks to the right specialized agent based on intent, channel, and context. It maintains state across the full interaction — even when the case spans multiple agents and multiple channels (chat to voice to human handoff). The customer experiences a single continuous interaction. The human sales rep receives the full case file: chat transcript, voice recording, CRM record, and QA analysis. Learn more about agent orchestration.
Want to build a 24/7 AI lead machine for your business? Explore the Growww AI Voice Engine, Chat/Voice Widget, and Supervisor Agent
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