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Results

6 hours to 1.
10-15% margin recovery.
Zero to 42% meeting booking.
A live dashboard in 10 days.

Every number on this page comes from a production system I built and a result someone measured. Construction, financial services, legal, nonprofit, distribution. Different industries, same pattern: scattered data in, working infrastructure out. Here's what changed.

Work-Smart.ai has built AI systems for mid-market companies across construction, financial services, legal, nonprofit, and distribution. Results include 10-15% margin recovery, 75% time reduction on document work, 0% to 42% meeting booking rate, and dashboard delivery in 10 business days. Every number is from a real engagement.

WHAT I'VE BUILT

Eight engagements. Eight different problems.One consistent starting point.

Concreto

Construction650 Employees

The problem

Running 7 active projects from a 10-tab Excel spreadsheet. Finding out about cost overruns 30 days after the fact. Losing 10-15% of project margins to manual processes the team had accepted as normal. The CEO couldn't answer "are we making or losing money?" without asking three people and waiting for a spreadsheet update.

What I built

Capataz, an AI system that searches across 10+ years of contracts, tracks project costs against actuals in real time, automates certification for compliance, manages workers across sites, and gives the executive team a dashboard showing every critical metric without spreadsheets.

The result

  • CEO sees every project's cost and schedule status in real time
  • Monday status meetings eliminated, the dashboard replaced them
  • Field teams report faster, finance catches overruns 3 weeks earlier
  • Document lookups went from 60 minutes to 30 seconds

Timeline

9 months (phased)

Investment

9-month phased engagement

Full AI Foundation Build details →

A $14B Wealth Advisory Firm

Wealth AdvisoryMiami

The problem

12 years of published research, 104 documents, and 77 podcast episodes. None of it visible to AI search. Prospects asking ChatGPT or Perplexity about wealth management never saw the firm. Branded searches worked. Everything else was a 71x gap. Fixing that opened conversations with every partner, and each one independently described the same six operational problems: proposals built from scratch, institutional knowledge trapped in email, meeting transcripts that disappeared after every call, and over $100K in AI tools deployed but never configured.

What I built

Voice DNA extraction from 12 years of firm content. Authority framework across 10 discovery questions prospects ask AI before calling. 60 structured authority pages written in the firm's calibrated voice. AI visibility gap closed from 71x to 2.1x within 90 days. Engagement expanded from a 6-week content project into a proposed 9-month Fractional Head of AI retainer to build proposal automation, a searchable knowledge base, meeting intelligence, and a daily briefing system.

The result

  • AI visibility gap: 71x reduced to 2.1x
  • AI search presence: from 2 of 10 industry queries to 8 of 10
  • Proposal time (projected Phase IV): 4 to 8 hours to minutes
  • Knowledge retrieval (projected Phase IV): unsearchable to seconds
  • Engagement type: Fractional Head of AI

Timeline

9 months (Fractional Head of AI)

Investment

9-month Fractional Head of AI retainer

Read the full case study →

Grupo Lyown

Legal ServicesMiami

The problem

Website scoring 8 out of 100 on performance. Leads from Google and Meta ads landed on a page that barely loaded, then went to a shared inbox where attorneys manually qualified every inquiry over WhatsApp. No CRM, no tracking, no way to know which leads converted or where they came from. Most never booked a meeting.

What I built

Victoria, a WhatsApp AI agent that qualifies leads automatically, books meetings into Calendly, and syncs everything to a new CRM with source attribution. Three service-specific landing pages replaced the broken site. Attorneys stopped manual WhatsApp within the first week.

The result

  • Meeting booking rate: 0% to 42% of inbound WhatsApp conversations
  • Lead response time: hours/next-day to seconds
  • Website performance: 8/100 to fully rebuilt with 3 landing pages
  • First client for Work-Smart.ai, came from a referral, led to everything else

Timeline

5 months to autonomous

Investment

Implementation + ongoing maintenance

See how AI agents work →

Joy of Impact

Nonprofit Consulting

The problem

Six custom ChatGPT bots, none connected to each other. Every client call meant hours of manual follow-up: summarizing notes, creating tasks, drafting emails. A 4-hour workshop generated 6 to 9 hours of documentation work. The founder and her VA were repeating context to AI tools that forgot everything between conversations.

What I built

Read everything she'd ever written, proposals, strategic plans, emails, workshop decks, and extracted a 280-line communication profile. Structured her entire process into a shared workspace with 15 reference documents and 7 pre-built AI skills (meeting debriefs, email composition, grant blueprints, newsletters, discovery call processing, proposal generation, and workshop creation). Her VA now runs the system independently.

The result

  • Grant blueprints from 6-8 hours to 2-3 hours
  • Meeting debriefs from hours of documentation to minutes
  • VA productivity increased, same person, same hours, 3-4x more output
  • First standalone training/workshop client for Work-Smart.ai

Timeline

2-3 weeks

Investment

Quick-turnaround setup

Learn about AI Training →

Rudolph Architecture

Architecture

The problem

Three divisions (Residential, Office, Revalue) with no unified digital presence. No client portal. No admin dashboard. No CRM connecting leads, projects, and analytics.

What I built

Three optimized websites (one per division), a client portal where projects track milestones and get automatic progress summaries, an admin dashboard that connects leads, projects, and revenue in one view. Included training on how to use AI tools for future operations.

The result

  • Unified digital presence across three divisions
  • Client portal replaced manual update emails
  • Admin dashboard provides single-view operations
  • Team trained on AI tools for ongoing use

Timeline

4 weeks

Investment

Implementation + ongoing maintenance

Packaging Manufacturer

Distribution & Manufacturing40 years old, 4 countries

The problem

Website down half the time. A field sales team across 4 countries with no digital selling tools. Reps carried physical catalogs. No career portal despite constant hiring.

What I built

An integrated digital platform where sales, catalog, customer operations, and lead capture run from one place across all four markets.

The result

  • Digital credibility restored across all four markets
  • Field sales team selling from one unified system
  • Hiring pipeline consolidated into a single workflow
  • Inbound leads captured automatically into the same platform

Timeline

Project-based engagement

Investment

Project-based

Almaga

Coaching Platform

The problem

Running a membership business on separate tools. Website on Squarespace. Membership on Memberful. CRM scattered across email. No content hub. Booking through Calendly with manual CRM entry.

What I built

A unified platform: website, membership billing, content hub, booking system, and CRM all talking to each other. Leads get qualified automatically, booked, and tracked, no manual re-entry.

The result

  • Everything managed from one place
  • No more manual data entry between systems
  • Business owner reclaimed operational hours

Timeline

3 months

Investment

Platform implementation

Industrial Parts Distributor

Distribution & Wholesale, USAnonymized

The problem

Tens of thousands of SKUs across multiple US distribution territories, all analytics running through Excel pivot tables connected to a legacy on-premise ERP. Getting a sales breakdown by territory, customer, or SKU meant hours of manual filtering. Leadership asked one question and got three different answers.

What I built

A real-time sales dashboard pulling directly from the legacy on-premise ERP. Leadership sees sales by territory, customer, product, and salesperson, in units. Daily automatic updates. Still exportable to Excel for teams who prefer it.

The result

  • Report generation from hours of filtering to seconds (page load)
  • One shared dashboard replaced individual Excel files across the team
  • Number consistency, one source of truth instead of three different answers
  • 10 business days from kickoff to live dashboard
  • Foundation set for AI layer: anomaly detection, purchasing suggestions, inventory alerts

Timeline

10 business days

Investment

Quick-turnaround dashboard + ongoing maintenance

See the AI Ops Audit →
EVIDENCE

Before and after.

10 days

Dashboard delivery (Industrial Parts Distributor)

kickoff to live

0% → 42%

Meeting booking rate (Lyown)

same ad spend

60 min → 30 sec

Document lookup (Concreto)

120x faster

6-8 hrs → 2-3 hrs

Grant blueprints (Joy of Impact)

75% time reduction

MetricBeforeAfter
Project margin visibility30-day lagReal-time
Authority content productionWeeks per piece (manual)Minutes per piece (calibrated AI)
Meeting booking rate0%42%
Document lookup60 minutes30 seconds
Grant blueprints6-8 hours2-3 hours
Branded vs non-branded CTR gapRoughly two orders of magnitudeBeing closed with 30 authority pages
Sales report generationHours of filteringSeconds (page load)
Dashboard deliveryKickoff10 business days
WHAT EVERY ENGAGEMENT HAS IN COMMON

Different industries. Different scales. Different budgets. The pattern underneath is the same.

01

Data was scattered. Excel, email, WhatsApp, disconnected tools. Nobody had a single source of truth.

02

Manual processes were eating hours. Reports, proposals, intake, qualification, work that AI handles in seconds was consuming days.

03

The executive team couldn't see what was happening. Visibility required asking people, not looking at a dashboard.

04

Previous attempts had failed. Bought tools nobody used. Got quoted $400K by a consulting firm. Tried a pilot that went nowhere.

05

The fix started with data, not tools. Every engagement began by consolidating the data layer. AI on broken data produces broken answers.

This is your Custom AI Operating System in practice. Six layers, built inside your company, owned by your team, in the order your operation needs them.

Common Questions

Questions About These Results

I measure what changes after the system goes live. Time saved on manual processes, margin recovered from better visibility, conversion rates on leads that used to fall through cracks. Every metric on this page comes from a real engagement, not a projection. The diagnostic identifies your specific metrics before we build.

First working system ships in 4-8 weeks. A construction company saw margin improvements within the first month of dashboard adoption. A law firm went from 0% to 42% meeting booking rate after a 2-month foundational build. The phased approach means you start seeing value before the full project is complete.

These results come from companies with 20-650 employees across construction, legal, financial services, distribution, nonprofit, and professional services. The pattern, scattered data, manual processes, no visibility, is the same regardless of size. If your CEO cannot get answers without asking three people, the framework applies.

The diagnostic exists to prevent that. Before any build starts, I map your data, processes, and specific pain points. The build scope comes from real operational problems, not from a feature list. Every engagement in the results above started with a diagnostic that identified exactly what to fix. That is why the systems work.

Yes. The AI Ops Audit (a fixed-fee 2-4 week diagnostic) is designed exactly for that. It gives you a complete picture of your operation in 2-4 weeks, and the audit fee applies toward the build if you move forward. An industrial parts distributor went from zero dashboard to live sales analytics in 10 business days.

Every company on this page started where you are. They knew something needed to change. They just needed someone to diagnose the problem and build the fix.

Start with a conversation. 30 minutes. I'll ask what hurts, listen for what's underneath, and tell you whether I can help. No pitch. No pressure. If there's a fit, I'll tell you how. If there isn't, I'll tell you that too. Want to understand the investment first? See what AI consulting costs.