CASE STUDIES & EVIDENCE

Systems presented at the level the evidence supports

Verified implementations, operating experience, portfolio builds, and reference architectures. Each case states what exists and where confidentiality limits the public claim.

EVIDENCE KEY

Verified implementation means the system and implementation artifacts exist.

Representative operating experience means the work is real but client publication permission or quantified results are not yet available.

Portfolio build means the working system was built internally rather than deployed as a named client engagement.

Reference architecture demonstrates a buildable pattern and is not presented as a client result.

01 / ProblemCall activity, transcripts and borrower information were separated from the CRM process, creating duplicate work and unreliable follow-up context.

02 / Control builtThe workflow receives Zoom recording and transcript events, separates inbound and outbound calls, normalizes phone identities, retrieves transcripts securely, finds or creates the matching Shape record, extracts approved borrower and loan information, and writes structured notes and follow-up context back into the CRM.

03 / Operating resultConnected completed calls and transcripts to the corresponding CRM lead and notes workflow.

01 / Mortgage & lendingVerified implementation

Mortgage Transcript-to-CRM Operating System

A production-shaped workflow connecting Zoom Phone calls, transcripts, borrower context, AI analysis and Shape CRM updates.

01 / ProblemOperational and commission data was distributed across grouped spreadsheets, multiple years and legacy structures that were difficult to import, reconcile and compare.

02 / Control builtThe project normalized clients, payments, KPI records and agents into linked Airtable tables, mapped legacy Kintone and Excel data, and implemented approved commission formulas and management interfaces.

03 / Operating resultCreated a shared relational structure for client, payment, KPI and agent records.

02 / Commercial insuranceVerified implementation

Insurance KPI & Commission Control Layer

A normalized Airtable operating database for clients, payments, agents, commissions and executive KPI reporting.

01 / ProblemCustomer details and the latest conversation context were not consistently available to the internal team after a website-chat interaction.

02 / Control builtThe workflow captures name, phone and email, stores the lead, creates an internal notification containing the latest message and conversation link, and prepares the data for downstream follow-up and visitor-intelligence workflows.

03 / Operating resultCreated a structured handoff from chatbot conversation to internal follow-up.

03 / Home servicesRepresentative operating experience

Home-Services Lead & Conversation Operations

A GoHighLevel workflow capturing chatbot leads, preserving conversation context and routing actionable details to the operating team.

01 / ProblemOperational data existed across forms, sheets and Airtable, but retrieving answers or preparing actions still required manual filtering and context switching.

02 / Control builtA conversational React interface routes natural-language questions through n8n, queries structured Airtable data, returns grounded answers, and can prepare email drafts and operational summaries.

03 / Operating resultCombined natural-language retrieval, KPI context and email drafting in one interface.

04 / Cross-industryPortfolio build

AI Query Handler & Operations Workbench

A React and n8n interface that turns natural-language operating questions into grounded Airtable answers and action drafts.

01 / ProblemVisitor exports contained repeated identities, inconsistent phone formats, multiple emails and phones in single fields, and company and skip-trace data that could not be imported safely as-is.

02 / Control builtThe pipeline deduplicates by UUID, normalizes phone numbers, selects primary values, preserves additional contacts, maps personal and company attributes, and outputs one predictable CRM-ready schema.

03 / Operating resultProduced a consistent CRM-ready schema from irregular visitor and enrichment exports.

05 / Lead generationPortfolio implementation

AudienceLabs Pixel Data Pipeline

A normalization and deduplication pipeline converting high-volume website visitor exports into CRM-ready lead records.

01 / ProblemRevenue and meeting events entered through separate platforms, while enrichment, context, routing and reporting were handled manually.

02 / Control builtThe architecture uses webhook events from Stripe and Calendly, enriches people and companies through Apollo, creates AI-assisted context, writes structured records to Airtable and Sheets, and sends the responsible team a Slack notification after controlled waits and checks.

03 / Operating resultCreated one event-driven path across payment, meeting, enrichment and internal notification systems.

06 / GTM operationsReference architecture

Multi-Channel Lead Engine

An event-driven lead operations system connecting payments, meetings, enrichment, AI context, Airtable, Slack and reporting.