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Proof-of-Work System
AI Lead Intake & Follow-Up System for an Advisory Firm
A lead operations system designed around a realistic service-business workflow where inquiries are captured, summarized, qualified, routed, followed up, and tracked.
Industry: Consulting / Advisory / Professional ServicesBuilt around a realistic business workflow to show how I map, structure, automate, document, and present operational systems.
Case Study Artifacts
A serious intake system is more than a form.
This proof-of-work system shows how I would structure, automate, document, and hand off this workflow for a real operating team.
Industry context
Advisory firms often receive inquiries that differ widely in urgency, budget, fit, and readiness. A good system needs to capture nuance without slowing down response time or hiding the next action.
Workflow problem
Leads can arrive from several channels, then sit in inboxes or chat threads. Without structured fields and reminders, the team has no reliable way to know what was answered, what needs review, or what should be followed up.
Starting point
The build starts with an inquiry, source channel, service interest, urgency, timeline, business context, qualification notes, assigned owner, and required next action.
- Capture core details once, then reuse them across the workflow.
- Summarize long inquiries without losing business context.
- Keep every automated draft behind a review state.
System architecture
The architecture makes the pipeline visible from first inquiry to follow-up completion.
Capture Intake form and channel records
Summarize AI-generated brief and fit notes
Route Priority, owner, service lane
Follow up Draft reply, reminder, status view
Automation map
The system prepares the handoff and follow-up path while preserving human judgment.
Inquiry received Create lead record
Summary drafted Extract context and request
Fit scored Apply qualification rules
Owner assigned Route by service lane
Reply prepared Draft response for review
Reminder set Track next action
Database schema
The database is designed around operational decisions, not vanity fields.
TableKey FieldsViewsReason
LeadsSource, service, urgency, fit, owner, statusNew, review, active, nurtureCentral pipeline record
InteractionsEmail, call notes, summary, reply linkBy lead and datePreserve communication history
TasksNext action, due date, owner, blockerDue today, overdue, waitingPrevent follow-up gaps
RulesService lane, priority, route, reply toneAdmin reviewKeep automation governed
SOP/checklist preview
- Confirm source channel, contact details, and service request.
- Review AI summary against the original inquiry before routing.
- Check fit score, urgency, timeline, and any missing context.
- Approve or edit the reply draft before sending.
- Set owner, next action, due date, and follow-up stage.
AI prompt library preview
Lead Summary
Summarize request, urgency, decision context, missing information, and recommended next action.
Qualification Notes
Score fit using the service criteria, then explain the score in operational language.
Reply Draft
Draft a concise response that confirms the request, asks for missing details, and proposes the next step.
Dashboard mockup
The dashboard makes lead health visible without requiring someone to search across tools.
New inquiries18Awaiting review
Pipeline board New, qualified, reply drafted, contacted, follow-up due, nurture, closed.
Follow-up due7Need owner action
Lead sources Website, referral, email, social, landing page.
Stalled records Missing context, no owner, overdue reply, review required.
QA controls
- Outbound replies stay in draft until reviewed.
- AI summaries link back to the original inquiry.
- Low-confidence fields are flagged for human clarification.
- Owner, due date, and next action are required before completion.
Implementation notes
I would implement the first version with a structured form, lightweight CRM database, AI summary prompts, route rules, notification triggers, a task view, and a follow-up dashboard for daily review.
Proof
What this system proves
I can design a lead workflow that captures useful context, gives AI a narrow role, preserves review, and turns follow-up into an accountable operating process.
Next Build
What I would build next
Calendar scheduling, pipeline aging reports, service-specific intake branches, reply tone variants, and a weekly conversion review by source and service lane.
Operating Value
Built for clarity
The strength is in the handoff: the right summary, the right owner, the right next action, and a dashboard that shows where attention is needed.
Let’s Build Your System
Need a lead intake system with real operating structure?
Bring the intake, qualification, replies, reminders, and pipeline into one cleaner flow.