Introduction

Lemar is a real-estate agency handling a high volume of enquiries across web forms, property portals, and messaging. Leads arrived faster than the team
could respond, and many went cold before anyone followed up. Monolythic Tech built an AI-driven lead workflow that captures, qualifies, and routes every
enquiry automatically, so agents spend their time on prospects who are ready to talk.

Project Goals

Capture every inbound lead from all channels in one place

• Qualify leads automatically against clear, agreed criteria

• Trigger fast, personalised follow-up without manual effort

• Surface the most promising leads to the team first

• Keep a human in the loop for high-value enquiries

Challenges

1. Fragmented sources: leads came from forms, portals, and messaging in different formats

2. Inconsistent qualification: criteria lived in people's heads, not a repeatable process

3. Speed vs accuracy: fast auto-replies risked sounding generic or mishandling nuance

4. Trust: the team needed confidence no real buyer would be dropped or mis-routed

5. Integration: everything had to flow into the agency's existing CRM

Process

• Research & Discovery: mapped how leads entered the business, where they stalled, and what "a good lead" meant to the team.

• Workflow Mapping: modelled the journey from enquiry to qualified hand-off, with clear decision points and follow-up rules.

• Agent & Retrieval Design: designed an AI agent grounded in listings and FAQs via RAG, so replies were accurate and on-brand.

• Build & Integration: built the flow in n8n, connecting channels, the LLM agent, and the CRM into one reliable pipeline.

• Evaluation & Hardening: instrumented the agent with Langfuse to trace and evaluate responses, tuning prompts and adding human-in-the-loop checks before
  go-live.

Key Features

• Unified lead capture across web, portals, and messaging

• Automated qualification against agreed criteria

• Personalised follow-up grounded in real listing data

• Priority routing of warm leads to the right agent

• Human handoff for high-value or unusual enquiries

• CRM sync so every lead and interaction is logged

Outcomes

• The team focuses on qualified, ready-to-talk prospects instead of raw triage

• Follow-up happens in minutes, not hours, cutting leads lost to delay

• Qualification is consistent, no longer dependent on who is on shift

• The agency has clear visibility into lead flow and performance

Conclusion

By turning a manual, leaky process into a reliable AI workflow, Lemar reclaimed time and stopped losing buyers to slow follow-up. The project shows how AI
agents, grounded in real data and properly evaluated, can take on routine work while leaving judgment calls to the people who do them best.