AI & Digital Transformation Consultant

From AI interest to AI adoption.

Enterprise transformation professional who designs and implements intelligent operational systems and workflow automation. 15+ years delivering technology and business transformation across Fortune 100/500 financial services — discovery, requirements, use-case definition, solution design, roadmap, implementation, adoption. Now building the systems myself: production AI workflows running in the field today.

Portrait of Dameon Pizano
15+ yrsTransformation delivery — Fortune 100/500
100+AI opportunities evaluated and prioritized
70 hrsWeekly manual work eliminated across clients
15SMB AI-readiness assessments delivered
Selected work

Three systems, same delivery pattern

Identify the business problem. Design the solution. Build the automation. Measure the outcome. Each of these runs in production today.

Case 01 · Personal operations
Python · Claude API · Google Sheets

Automated job discovery and intelligence pipeline

A fully automated job search system that scrapes, scores, and organizes relevant listings into a structured tracker — eliminating 20 hours of weekly research and replacing it with a daily curated feed of pre-qualified opportunities.

Problem

2–3 hours a day disappeared into manually searching job boards and career sites, reading descriptions to decide what was worth applying to. Listings were irrelevant, duplicated, or missing key details — and with no tracking system, opportunities were lost simply because they were found too late.

Solution

A scheduled pipeline that pulls listings from target company career pages via scraping and job board APIs, uses Claude to score each role against a custom fit rubric, writes qualified results to a Google Sheet, and delivers a daily email digest of new matches.

Process flow
How it works
  • InputDaily scheduled trigger pulls fresh listings via career site scraping and job board APIs.
  • FilterA pre-scoring filter removes obvious mismatches before AI scoring — keeping cost low and signal high.
  • AI scoringClaude evaluates each new listing against a structured rubric and returns a 0–100 score with a written rationale.
  • VerdictsScores auto-bucket into APPLY NOW, REVIEW, or SKIP.
  • RoutingQualified listings are written to a Google Sheet with title, company, score, rationale, and apply link.
  • OutputDaily email with APPLY NOW and REVIEW roles — or an all-clear when nothing new surfaces. Failure alerts fire automatically.

Outcome

  • 20 hours per week of manual research eliminated
  • Daily search time cut from 2–3 hours to under 30 minutes of digest review
  • Pre-scored, justified listings surfaced daily with zero manual browsing

Stack

PythonClaude APIJob board APIs Web scrapingGoogle Sheets APIGmail SMTP Scheduled executionAutomated test suite

AI skills demonstrated

Prompt engineeringLLM API integration AI cost optimizationAI output validation AI system designWorkflow automation Structured data + AITest-driven AI development
Case 02 · Client engagement
n8n · Claude API · HubSpot · Slack · Notion

Multi-agent CRM and workflow automation

A multi-agent orchestration system that eliminated roughly 50 team hours per week of manual CRM updates, task routing, and internal notifications for a client — freeing staff capacity for higher-value work through AI-driven decision logic and API integrations across HubSpot, Slack, and Notion.

Problem

The client's team spent roughly 50 hours per week, across the team, manually updating CRM records, routing tasks, and sending status notifications. The work required no real judgment, but consumed significant staff time and was consistently error-prone.

Solution

A multi-agent n8n workflow that monitors triggers across the client's tool stack, uses Claude to interpret context and determine the correct action, then executes updates automatically across CRM, Slack, and Notion without human intervention.

Process flow
How it works
  • InputTriggers fire from Gmail, Google Calendar, and HubSpot activity throughout the day.
  • InterpretationClaude reads the triggering content and determines the correct downstream action — which record to update, which task to create, and who to notify.
  • Executionn8n executes the actions via API across HubSpot, Slack, and Notion for task and project tracking.
  • LoggingEvery automated action is logged with timestamp, action taken, and source trigger for client review.
  • OutputCRM stays current in real time; tasks and notifications route themselves. The client reviews a daily action log instead of performing the work.

Outcome

  • ~50 team hours per week of manual admin work eliminated
  • ~$80K estimated annual client savings
  • CRM accuracy improved — no missed updates from manual entry lapses
  • Staff time redirected from repetitive tasks to higher-priority work

Stack

n8nClaude APIHubSpot API Gmail APIGoogle Calendar APINotion API Slack APIGoogle Sheets

AI skills demonstrated

Multi-agent orchestrationContext-aware decision logic API integration + automationAgentic workflow design Prompt engineeringOperational AI implementation Human-in-the-loop design
Case 03 · Client engagement
n8n · Claude API · Twilio · HubSpot

Automated email and SMS follow-up with AI personalization

A multi-channel follow-up system that sends AI-personalized email and SMS sequences to leads after initial contact, keeping prospects engaged through the decision cycle without any manual outreach effort.

Problem

The client followed up with leads inconsistently and by hand. High-intent prospects who didn't convert immediately went cold because there was no structured follow-up process. Outreach was generic and poorly timed, which hurt response rates.

Solution

An automated email and SMS follow-up system triggered by lead intake. Claude generates personalized message content based on the lead's inquiry details and funnel stage; n8n handles sequence timing and channel routing.

Process flow
How it works
  • InputA new lead enters the pipeline via form submission or CRM trigger.
  • PersonalizationClaude generates email and SMS copy tailored to the lead's specific inquiry, industry, and funnel stage.
  • Sequencen8n sends a structured follow-up sequence across email and SMS at defined intervals over 7–14 days.
  • BranchingThe sequence pauses automatically if the lead replies or books a meeting, preventing over-communication.
  • OutputEvery lead receives consistent, personalized follow-up with zero manual outreach. Engagement activity logs to the CRM automatically.

Outcome

  • Outreach cycle reduced from 72 hours to roughly 5 minutes
  • Lead conversion increased 40% against the pre-automation baseline
  • Manual follow-up effort eliminated across all active leads

Stack

n8nClaude APITwilio (SMS) Gmail APIHubSpot APIWebhook triggers

AI skills demonstrated

Prompt engineeringDynamic content personalization Multi-channel automationAgentic workflow design CRM integrationFunnel automation LLM API integration
How I work

Transformation discipline, applied to AI

The technology changed. The method didn't. Every system above followed the same four steps.

01
Find the real problem

Start with where hours actually go, not with the tool. Most "AI problems" are process problems wearing a costume.

02
Design the smallest system

Deterministic logic where it works, AI only where judgment is genuinely needed. Cheaper to run, easier to trust.

03
Build and instrument it

Every action logged, every failure alerted, outputs validated before they touch a system of record.

04
Measure what changed

Hours returned, errors avoided, dollars saved. If the number isn't there, the system isn't done.

Background

Fifteen years of transformation delivery — now building it

I've spent my career taking initiatives from discovery through adoption at Fortune 100 and 500 financial services organizations — requirements and use-case definition, solution design, roadmap development, implementation, and the change management that decides whether any of it actually gets used. Big 4 consulting at Deloitte and Accenture; before that, enterprise technology and analytics roles inside the banks themselves.

The through-line is the same in every role: find a manual or inefficient process, design something better, and get people to adopt it. AI didn't change that pattern — it gave me a much sharper tool for it. The recent focus is enterprise AI readiness and GenAI-enabled workflows, plus independent builds using Claude, Claude Code, and agentic orchestration.

I'm not an engineer and don't claim to be. I evaluate, select, and integrate AI tools at the product layer — model capability, prompt reliability, output quality, failure modes — and coordinate the people who build the rest.

Experience
9/2025 — Present
AI & Digital Transformation Consultant
Independent AI Consulting · Los Angeles, CA

AI-readiness assessments spanning workflow suitability, data and technology readiness, integration, and governance — roadmaps and proof-of-concept solutions delivered for 15 SMBs, 10 converted into paid implementation engagements. The three systems above came out of this practice.

7/2022 — 9/2025
Consultant, Technology Strategy & Transformation
Deloitte Consulting LLP · Los Angeles, CA
  • Established a value, feasibility, data-readiness, and governance framework to evaluate 100+ AI opportunities — document processing, case summarization, knowledge retrieval, workflow automation — supporting investment and go/no-go decisions
  • Facilitated 20+ business and technology workshops across a 30-application environment, mapping workflows, pain points, data needs, and system dependencies to prioritize AI and automation opportunities
  • Translated business needs into 50+ requirements and future-state process models for AI-enabled document processing — intake, classification and extraction, routing, human review, downstream orchestration
  • Reduced case-resolution time ~20% and supported ~$1.2M in cost avoidance by managing five workstreams and coordinating delivery across 10 operational teams over 18 months
  • Developed AI adoption and governance recommendations with operations, risk, compliance, customer service, and technology leaders — human oversight, training, workforce readiness, operating-model change
11/2016 — 10/2020
Consultant, Digital Transformation & Automation
Accenture · Chicago, IL
  • Identified automation opportunities representing ~$2M in projected savings by assessing processes for manual effort, repeatability, business value, feasibility, and controls — converting findings into a prioritized automation backlog
  • Reduced SOX compliance review time 60% and enabled remediation 30 days early by delivering an RPA solution that automated audit-evidence collection and review
  • Reduced manual approval-processing effort 60% by leading RPA adoption through stakeholder communications, end-user training, SOP development, go-live support, and hypercare
  • Enabled secure loan-program access for 5,200+ financial institutions by translating business and security requirements into configuration requirements and operating procedures for the SBA Paycheck Protection Program
10/2015 — 11/2016
Senior Business Analyst, Enterprise Technology
Bank of America · Chicago, IL

Automated access-lifecycle processes across 80+ banking applications by translating business and control requirements into low-code workflows and coordinating development, testing, implementation, and change management.

11/2014 — 10/2015
Systems Analyst, Trade Operations
Options Clearing Corporation · Chicago, IL

Strengthened operational controls supporting approximately $100B in daily transactions by developing and refining SQL-based data-transfer processes and remediating issues identified through SEC audit activities.

8/2011 — 11/2014
Risk Analyst — Portfolio Analytics
Bank of Montreal (BMO) · Chicago, IL

Identified approximately $5M in potential loss exposure by developing SQL-based portfolio analytics models later adopted as a department-wide analytical standard.

Education
B.A., Finance & Business Administration
St. Ambrose University · Davenport, IA
Skills

AI transformation & GenAI

AI Strategy & ReadinessAI Use-Case Prioritization Business Value & Feasibility AssessmentAI Solution Design Responsible AI & GovernanceAI Adoption & Change Management Generative AIAgentic AI Clauden8n

Transformation & delivery

Digital TransformationProcess Transformation Requirements EngineeringSolution Design Current / Future-State Process MappingAgile / SDLC UAT & TestingProgram & Workstream Management Stakeholder Management

Enterprise platforms & technology

Microsoft Power AutomateUiPathServiceNow SalesforcePower BIMicrosoft 365 REST APIsSQLJira ConfluenceAzure DevOps
Contact

Let's talk about the work

Open to AI and digital transformation roles, program and product delivery roles, and consulting engagements building systems like the ones above.