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Data Leader · Analytics · Engineering · Intelligence

Thiago Andrade

Data Engineering · Analytics · BI · Marketing Analytics · Automation

Builds analytics capabilities from concept to production — consistently, across industries, for thirteen years. Co-established the Central Analytics function at Boeing. Designed Nova Scotia Health's COVID-19 PPE supply-demand platform, delivering real-time intelligence that shaped provincial policy. Stood up a full Lakehouse and AI automation environment serving 450+ stakeholders, and pioneered automated guest intelligence systems years ahead of the industry. Full-cycle across the entire analytics value chain — architecture, engineering, prototyping, and executive decision-support — with 5+ years managing teams while staying hands-on. Technical enough to build it. Analytical enough to validate it. Strategic enough to make it matter.

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15+
Years of Experience
24+
Portfolio Projects
4+
Frameworks
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Building data capabilities,
not just reports.

I'm a senior data and analytics leader who operates at the intersection of engineering, strategy, and design. My work spans end-to-end data pipelines, machine learning prototypes, BI product development, and proprietary analytical frameworks built from the ground up.

I started my career in marketing analytics and CRM — building loyalty programs, customer segmentation models, and campaign measurement systems. That foundation shaped how I think about data: always in service of a business decision, always connected to the customer journey. Over time, my scope expanded into data engineering, automation, OCR, Power Platform development, and AI integration.

I specialize in operationalizing analytics: taking a concept from whiteboard to production-ready tool, whether that's an AI document extraction pipeline, a CRM analytics model, a Power Platform application, or a governance framework adopted across business units.

My design philosophy: data products should be as polished as consumer software — clear, trusted, and built to last beyond the team that created them.

15+
Years — Marketing Analytics → Data Engineering → AI/Automation
7+
Years in Marketing Analytics, CRM & MarTech
4
Original frameworks designed and deployed org-wide

A full-stack analytics skill set.

⚙️
Data Engineering
ETL / ELT PipelinesSQL (Advanced)Data ModelingSnowflake / BigQueryPythonData LineagedbtPipeline Automation
📣
Marketing Analytics & CRM
Customer SegmentationLoyalty AnalyticsCampaign MeasurementCRM (Salesforce)Direct MarketingMarTech StackROI ModelingA/B TestingCohort Analysis
📊
BI & Visualization
Power BITableauTableau PrepDAX / M QueryDashboard DesignKPI FrameworksData Storytelling
🤖
Machine Learning & OCR
Predictive ModelingClassificationNLP / Text AnalyticsDocument ExtractionAI-Powered ParsingPrompt EngineeringModel Validation
Power Platform & Automation
Power AppsPower AutomateSharePointMicrosoft 365Workflow DesignApp Prototyping
🏛️
Strategy & Leadership
Data StrategyData GovernanceMaturity ModelingExecutive CommunicationTeam LeadershipStakeholder Management

AI Applied Projects

Full-stack AI product design and architecture. From concept through deployment — leveraging Claude and Gemini to build production systems that synthesize complex data and deliver measurable intelligence.

Talent Intelligence

SHRINK.AI

AI career intelligence tool that synthesizes multi-format personality assessments (Gallup, DISC, Wingfinder, TriMetrix) into a unified talent profile and scores candidate fit against any job description.

Zero-Data Retention PDF Parsing LLM Integration Multi-Framework Synthesis
Launch Tool
Interview Coaching

Vantage Interview

AI-powered mock interview platform performing semantic matching between your resume and target job descriptions. Real-time coaching, targeted feedback, improvement guidance.

Resume Parsing JD Matching Real-Time Feedback Coaching Architecture
Launch Tool
Language Learning

Maître

End-to-end conversational AI French learning platform. Full curriculum architecture with adaptive feedback model and AI-directed instruction applying pedagogical design principles.

Curriculum Design Adaptive Learning Conversational AI Gemini Integration
Launch Tool
Conversational Intake

AI Contact Form

A reusable conversational intake pattern replacing the static contact form. An agent chats with the visitor to gather name, company, and reason for reaching out, then hands off a pre-filled WhatsApp or LinkedIn message.

Multi-Turn Dialogue Structured Extraction Serverless Function Claude Integration
Try It Below
Dev Tooling

Agentic Dev & Deploy Pipeline

This entire site is built, versioned, and deployed through an AI-native workflow — Claude Code wired directly into GitHub and Netlify via MCP, turning plain-language requests into committed code and live deploys with no manual handoff in between.

Claude Code + MCP GitHub Integration Netlify Integration Zero-Touch Deploy
View the Repo

Work that ships.

Data EngineeringML / AIOCR
01
AI Document Extraction — Architecture

End-to-end architecture for an AI-powered document intelligence pipeline. Covers OCR ingestion, extraction logic, validation layers, and output normalization at enterprise scale.

4-layer pipeline: Document ingestion → AI extraction engine → Validation gate → Output delivery
Small language model (3.8B params) running batched inference with 8 prompts per call, fully in-tenant
3-tier confidence routing: Tier A auto-approve → Tier B standard review → Tier C deep review
35-field unified schema supporting multi-row output across 4 document types
Full/incremental refresh modes with Power Automate-triggered ingestion from email and SharePoint
View evidence ↗
BI & Analytics Data Engineering Automation
02 LIVE PRESENTATION
Rethinking How We Build With Data

A full analytics modernization initiative for HFC Ops at HUB International — replacing siloed, single-tool Excel dependence with a governed, automated notebook-engine architecture. One shared source of truth in place of five conflicting versions of the same number.

93% of AP Queue processing time saved — 12 minutes down to 1 minute per refresh, fully SOX-audited
97.5% pipeline refresh time reduced, with zero copy-paste errors and 100% reproducibility
25,000+ employee records automated end-to-end, replacing manual exports and shadow documentation
Forecast model competition framework: 4 statistical models run in parallel, best model auto-selected by accuracy each cycle
Full audited architecture: orchestration → source systems → notebook engine → governed data → consumption
Launch the 14-slide deck ↗
Data EngineeringStrategy
03
Data Access Modernization — Strategic Proposal

Business case and phased roadmap for transitioning from third-party data dependency to direct, governed database access. Covers ROI, architecture, and AI acceleration strategy.

Data maturity leap framing: from vendor-mediated access to owned, queryable infrastructure
Multiple integration points mapped: source systems, transformation layers, and consumer endpoints
Automation at scale: eliminating recurring manual extract-and-load cycles
Accuracy by design: validation and reconciliation built into the access layer, not bolted on after
Phased implementation roadmap with ROI model and AI acceleration use cases
View evidence ↗
Data EngineeringAutomation
04
BPO Workforce Forecast System

Interactive flowchart of a workforce forecasting system built for BPO operations. Covers data ingestion, model logic, scenario simulation, and downstream reporting integration.

18-month historical transaction data ingested per workflow — grouped by team (onshore/offshore)
Smart forecasting engine: projects transaction volume per workflow, then calculates FTE requirements
Shrinkage model: accounts for unavailable hours (training, leave, breaks) before FTE conversion
Scenario simulation: allows planners to test volume assumptions against staffing outcomes
Connects forecast outputs to downstream reporting; offshore staffing managed separately by design
View evidence ↗
Data Engineering
05
Data Extraction Pipeline — Architecture Diagram

Technical architecture diagram for a structured data extraction pipeline, mapping source ingestion through transformation layers to reporting outputs with full lineage visibility.

Visual lineage diagram: source systems → extract → transform → load → reporting consumers
Annotated flow showing data handoff points, ownership boundaries, and refresh cadence
Designed for stakeholder alignment: technical enough for engineers, readable for business owners
Highlights incremental vs. full refresh patterns and failure-handling design decisions
View evidence ↗
BI & Analytics
06
Operational Quality Report — Zero-Value Analysis

Automation proposal replacing a daily manual Excel macro process. Identifies accounts where debits and credits cancel out — enabling account clearance with zero manual steps.

Problem statement: daily manual Excel macro + cross-referencing two reports → replaced entirely
Automated pipeline runs daily: same outputs, 0 manual steps, both CA and US regions unified
Full history preserved: audit trail maintained through automated run, not wiped on each refresh
Redesigned report layout: clear flagging of clearable accounts vs. accounts needing review
Requirements, output spec, next steps, and implementation timeline included
View evidence ↗
Power PlatformPrototyping
07
Operations Queue App — UX Prototype

High-fidelity UX mockups for a queue management Power App. Four tabs: Today's Queue, Previous Query, Reassigned Cases, and Help Needed — with full case management flows.

4-tab navigation: Today's Queue / Previous Query / Reassigned Cases / Help Needed
Card-based case list with inline filters: by name, status (Need Info / Need Setup / Not Worked), paygroup
Sort controls: by days in queue, name, amount, invoice date — with active/unassigned/help-needed counts
Case edit panel: slides in on card click with full status workflow and assignment controls
Bulk reassign: checkbox-select multiple cases and reassign in one action
View evidence ↗
Power PlatformAnalytics
08
Queue Analytics — Technical Recommendations

Technical spec and data architecture recommendations for migrating queue operations from Excel/notebook tracking to a governed SharePoint + Power Automate system.

Source analysis: what stays from the existing notebook model, what gets rebuilt in SharePoint
Design decisions: single list vs. multi-list, status lifecycle states, field naming conventions
Daily cycle redesign: how auto-population, assignments, and completions work in the new system
Connection map: which app screens connect to which SharePoint columns and which flows
Pre-build checklist: items to confirm before dev starts to avoid rework mid-build
View evidence ↗
Power PlatformPrototyping
09
Vendor Verification App — UX Prototype

Screen-by-screen prototype for a vendor verification Power App. Multi-step form UX covering company, banking, address verification, and final submission states.

Multi-section form: company info → banking details → address verification → review & submit
Progress navigation: section tabs with completion indicators and inline validation states
Banking verification flow: account number, routing, bank name with masked display on review
Submission states: pending, approved, rejected — with appropriate UI feedback per state
Case-level context panel showing vendor history and prior verification attempts
View evidence ↗
Power PlatformAutomation
10
Vendor Verification — Design Specification

Full technical design spec: SharePoint schema, approval automation flows, lifecycle states, and migration strategy for a vendor management system.

Architecture decision: single SharePoint list (BankVerification_Cases) vs. fragmented multi-list approach
Proposed column inventory: 30+ fields with data types, default values, and validation rules
Screen architecture: which Power Apps screens map to which list operations and flows
Approval automation: Power Automate flow design for multi-stage sign-off and notification logic
Migration strategy: how to move from the current 3-list setup without losing historical records
View evidence ↗
AutomationPower Platform
11
AP Vendor Control — Attachment Process Flow

Process flow for an AP vendor control app covering document attachment handling, validation routing, and downstream data capture for audit and compliance.

End-to-end attachment flow: upload trigger → type classification → validation check → route or reject
Document type branching: different validation rules applied based on attachment category
Downstream capture: validated attachments written to SharePoint with structured metadata
Audit trail design: every attachment action logged with timestamp, user, and status
View evidence ↗
AnalyticsStrategy
12
PACE Framework — Training Presentation

Interactive training deck for the proprietary PACE analytics methodology. Built to onboard analysts and stakeholders into a structured, repeatable approach to data-driven decision making.

Framework overview: the four PACE stages and how they connect prioritization to execution
Stage-by-stage walkthroughs with real scenario examples and anti-pattern callouts
Team enablement guide: how analysts apply PACE on day-to-day requests vs. strategic initiatives
Stakeholder-facing slides: how to present PACE to business owners to get buy-in on structured approach
Self-paced format: click-through navigation designed for async training without a facilitator
View evidence ↗
ML / AI Product Launch Strategy
13 LIVE PRODUCT
SHRINK.AI — Career Intelligence Tool

An AI-powered career profiling tool I designed and shipped. Upload your personality assessments — Gallup, DISC, Wingfinder, or any PDF — and AI synthesizes them into a unified talent profile, then scores your fit against any role or job description. Free, private, instant.

SHRINK = Self-profile HR Role Intelligence & Knowledge — AI that turns assessment PDFs into a structured career profile
Upload any combination of assessments (Gallup CliftonStrengths, DiSC, Wingfinder, TriMetrix, MBTI) — AI reads and synthesizes them in one pass
Role matcher: paste any job description and get a scored fit analysis grounded in your actual personality data, not just a résumé
Fully private — no data stored, no account required. All processing happens in-session
Export your synthesized profile as a shareable PDF — a living document that grows as you add more assessments
Visit shrinkai.netlify.app ↗
ML / AI Product Launch
14 LIVE PRODUCT
Smart Interview — AI Mock Interview Coach

An AI-powered interview practice tool I designed and shipped. Runs realistic mock interviews with voice interaction, tailors questions to your résumé and target role, and scores your answers with real-time feedback so you walk in prepared.

Voice-driven mock interviews — speak your answers, get transcribed and scored in real time
Résumé-aware question generation, tailored to the specific role you're preparing for
Structured feedback and scoring on each answer to sharpen delivery before the real thing
Free, private, no account required — all processing happens in-session
Visit vantage-interview.netlify.app ↗
ML / AI Automation
15 LIVE ON THIS SITE
AI Contact Form — Conversational Intake Agent

A reusable AI intake pattern I designed to replace static contact forms. An agent chats with the visitor to gather name, company, and reason for reaching out, then hands off a pre-filled WhatsApp or LinkedIn message — no forms, no back-and-forth.

Multi-turn conversational intake — one question at a time, feels like messaging, not filling out a form
Structured extraction: name, company, topic, and message captured as clean JSON once the conversation completes
Hands off to a pre-filled WhatsApp message or a copy-to-clipboard LinkedIn DM — the visitor hits send, not submit
Deployed as a Netlify serverless function proxying Claude — live on this site's Contact section and on powerofthe3ations.netlify.app
ML / AI Product Launch
16 LIVE PRODUCT
Maître — AI French Learning Companion

A conversational AI language-learning app I designed and built end-to-end. Live voice conversations with real-time pronunciation scoring, predictive vocabulary search, and cross-device sync — built as a full PWA with offline support.

Conversational AI practice partner with live mic input, text-to-speech replies, and real-time speech-alignment pronunciation scoring
Predictive vocabulary search with response caching and code-splitting to keep lookups instant
Cross-device sync for vocabulary, notes, and conversation history via Firebase
Installable PWA with offline app-shell caching and AI-action guardrails when offline
Visit maitre.ai.studio ↗
BI & AnalyticsStrategyFramework
17
PACE Framework

A structured analytics methodology for prioritizing, accelerating, and governing data initiatives across operational teams. Designed to move teams from reactive reporting to proactive insight generation.

Prioritize: triage incoming requests against business impact instead of first-come-first-served
Accelerate: standardized patterns cut repeat-analysis time on recurring request types
Govern: consistent definitions and ownership so metrics don't drift between teams
Also shipped as a dedicated training deck for analyst and stakeholder onboarding
View evidence ↗
Data EngineeringStrategyFramework
18
Data Enablement Model

An organizational framework for building in-house data capability — covering access governance, query ownership, documentation standards, and phased maturity progression from external dependency to internal ownership.

Maturity phases: from vendor-mediated reporting to owned, governed, self-serve data access
Access governance model: who can query what, and how ownership is assigned per domain
Documentation standards baked into the rollout, not bolted on after teams are already self-serving
Applied in full on the Rethinking How We Build With Data initiative above
View evidence ↗
AutomationAnalyticsFramework
19
Forecast-to-Actuals Automation Pattern

A reusable automation pattern linking workforce forecast models to operational actuals tracking, enabling continuous variance analysis without manual reconciliation across BPO and operations environments.

Closes the loop between forecast models and what actually happened, automatically
Continuous variance tracking replaces periodic manual reconciliation spreadsheets
Pattern generalizes beyond BPO — anywhere a forecast needs to stay honest against actuals
Same pattern underlies the BPO Workforce Forecast System above
View evidence ↗
PrototypingPower PlatformFramework
20
Prototyping-First App Design

A design approach for Power Platform development that leads with high-fidelity UX mockups and technical specs before any build begins — reducing rework and accelerating stakeholder alignment on scope and experience.

Mockups and specs come first — stakeholders sign off on the experience before a single flow is built
Cuts rework by catching scope and UX disagreements at the cheapest possible stage
Applied directly on the Operations Queue and Vendor Verification app prototypes above
View evidence ↗
ML / AI Prototyping HR Tech
21 CONCEPT
HR ML — Candidate Screening & Recommendation Engine

A machine learning system for screening resumes at volume and ranking candidates against role requirements — surfacing the strongest matches for a recruiter to review instead of manually triaging every application.

Structured extraction from résumés into a normalized candidate profile — skills, experience, tenure patterns
Role-fit scoring model that ranks candidates against a job's requirements, not just keyword overlap
Recommendation layer that surfaces the top-N candidates per role for recruiter review, with reasoning attached
Designed with bias-mitigation and auditability as first-class requirements, not an afterthought
Discuss this concept ↓
Strategy Prototyping Framework
22 LIVE FRAMEWORK
The Power of the 3 Ations

A tool-agnostic framework I authored — Communication, Documentation, and Integration — for why software teams actually fail and how to fix it. Built into a full site with an AI Q&A agent over the framework content and a conversational intake agent for connecting directly.

Grounded in real cost data: poor communication costs $1.2T/year (US) and causes 70% of project failures
Poor documentation costs $85B/year globally and consumes 33% of developer time (Stripe)
Tool integration speeds tasks 55% (GitHub/Microsoft) — the framework makes no assumptions about specific tooling
"Ask the Framework" AI chat answers questions about the methodology directly, in the visitor's own language
Visit powerofthe3ations.netlify.app ↗
Automation Prototyping Dev Tooling
23 CONCEPT
AI Tooling Integration — Editor to Jira & PM Systems

Extending the same AI-native workflow that builds this site into day-to-day engineering operations: VS Code and Claude Code wired directly into Jira, Confluence, and issue trackers via MCP, so tickets, code, and documentation stay in sync without manual status updates.

Claude Code's MCP already connects to 300+ tools out of the box — Jira, GitHub, databases, and more — the "Integration Ation" pillar of the framework above
Tool integration speeds tasks 55% (GitHub/Microsoft) — the gap is usually adoption, not capability
Ticket status, code state, and documentation update from one workflow instead of three separate manual habits
Proven pattern: this site's own Claude Code + GitHub + Netlify pipeline is the same integration model applied to deployment instead of ticketing
Discuss this concept ↓
Data Engineering BI & Analytics Philosophy
24 CONCEPT
Data Modernization Philosophy — Siloed Tools to Governed Notebooks

The transferable thesis behind the HUB International initiative above: one dataset should never live in isolation. A notebook engine as the single governed layer that ingests, validates, transforms, and audits — replacing five conflicting versions of the same number with one source everyone agrees on.

The siloed default — every team pulls its own copy, transforms it differently, stores it separately — is a choice, not a constraint
A single notebook-engine layer can ingest, validate, transform, apply business logic, write, and audit-log in one governed pass
Compliance and speed aren't a tradeoff when the audit trail is built into the pipeline, not bolted on after
Proven at scale in the full 14-slide case study above — 93% time saved, 25,000+ records automated
Launch the deck ↗

Does my profile fit
your role?

Don't make assumptions — test the fit directly. Paste a job description or pick the skills you need, and the AI will analyze the match against my full experience profile in seconds.

📋
Paste a JDDrop in any job description and get an instant match analysis — score, strengths, gaps, and a plain-English verdict written for a hiring manager.
🏷️
Pick TopicsNo JD? No problem. Select the skills or tools your role needs and get a tailored assessment of where I fit strongest.
Honest ResultsThe AI won't just say yes. You'll see matched strengths in green, potential gaps in red, and a candid narrative — so you can decide confidently.
Paste a Job Description or Describe Your Needs
or pick quick topics
Awaiting your input
Analyzing profile match…
Match Score
✓ Strong matches
△ Potential gaps
Assessment

How I think,
lead, and deliver.

These are real results from formal assessments — not summaries or approximations. They show how I process information, relate to others, approach challenges, and perform under pressure.

Gallup CliftonStrengths — Top 5
Thinking · Learning · Competing
Deliberative — Careful, vigilant, risk-aware. Identifies what can go wrong before it does. Approaches decisions with precision and reserve.
Learner — Energized by acquiring new skills. Thrives in dynamic environments where rapid upskilling is required.
Analytical — Data-driven and pattern-seeking. Challenges claims with evidence. Peels back layers to find root causes.
Focus — Goal-oriented and filters ruthlessly. Keeps teams on track and aligned to what matters most.
Competition — Performance-driven. Uses comparison as a motivator to push standards higher, in self and team.
Red Bull Wingfinder — Top 4 Strengths
Direct · Balanced · Adaptable · Open
Connections
Very Direct ★
Straight-talking and honest. Clear communicator, not influenced by others.
Connections
Very Balanced ★
Calm under pressure. Resilient. Keeps a cool head when stress levels rise.
Creativity
Highly Adaptable ★
Thrives with uncertainty. Flexible thinking. Responds well to change and novelty.
Creativity
Open to Experience ★
Imaginative and curious. Values diversity. Leaps enthusiastically into the unknown.
Drive
Confident Achiever
Comfortable in the limelight. Takes the lead and sets high standards for self.
Thinking
Agile Learner
Learns from both experience and theory. Analytical yet not robotic. Trusts instincts.
Formal Performance Review — Manager Level
Overall: Exceeds Expectation
Exceeds — Initiative — Takes on challenges with independence. Generates new ideas. Identified problems and drove change before being asked.
Exceeds — Integrity & Ethics — Described as "exceptional" and "unquestionable" by reviewing manager. Always straightforward and compliant.
Exceeds — Decision Making — Rated for systematic problem-solving, data integrity thinking, and managing competing priorities.
Exceeds — Dependability — Consistently delivers independently. Strong work ethic. Steps up when needed.
Consistent — Quality & Communication — Praised for accuracy, stakeholder focus, active listening, and concise presentation style.
TTI TriMetrix® Talent — Behavioral + Driving Forces
DC Profile · Intentional · Commanding
DISC — Natural Style: D=83, C=71 — High Dominance + High Conscientiousness. Results-driven, systematic, analytical, and precise. Takes charge while maintaining quality and rigor.
Primary Driver: Intentional (97) — Driven to help others with purpose and direction, not for the sake of helpfulness alone. Wants impact to be measurable and meaningful.
Primary Driver: Commanding (81) — Motivated by recognition, autonomy, and control over personal output. Works best in roles with real ownership and visibility.
Top Personal Skills — Using Common Sense (92), Theoretical Problem Solving (90), Integrative Ability (89), Persuading Others (89), Practical Thinking (88).
Intellectual Driver (60) — Energized by learning, acquiring knowledge, and discovering how things truly work beneath the surface.
📎 Full assessment PDFs available on request
Observable Work Patterns
🎯
Analytical & Deliberate
Challenges assumptions with data. Finds root cause before proposing solutions. Identifies risks others overlook — then plans around them.
↳ Gallup: Analytical + Deliberative
🔄
Adaptable Under Change
Thrives in ambiguous, fast-moving environments. Uncertainty boosts creativity rather than slowing output. Flexible across domains and industries.
↳ Wingfinder: Highly Adaptable (Top Strength)
📣
Direct Communicator
Straight-talking and clear. Asks good questions and presents a point of view in a confident, professional, informed manner. Rated highly by senior stakeholders.
↳ Wingfinder: Very Direct + Performance Review feedback
Independent & Dependable
Works independently exceptionally well. Moves projects forward with minimal input. Consistently exceeds delivery commitments without needing hand-holding.
↳ Performance Review: Exceeds — Dependability
🏆
Results & Competition-Driven
Motivated by performance benchmarks and measurable outcomes. Uses comparison to push personal and team standards higher. Wins with data, not volume.
↳ Gallup: Competition + Focus
🌱
Continuous Learner
Described as consistently demonstrating a "thirst for knowledge." Self-teaches across technical domains. Energized by onboarding new skills in short periods.
↳ Gallup: Learner + Performance Review feedback

The full stack.

Power BI
Tableau
Tableau Prep
SQL Server
Snowflake
Python
Power Apps
Power Automate
Salesforce CRM
SharePoint
Microsoft Fabric
Azure
Databricks
dbt
R / RStudio
Git / GitHub
Claude AI
DAX / M Query
REST APIs
Excel Advanced
Jira / Confluence
MarTech Stack
Power BI
Tableau
Tableau Prep
SQL Server
Snowflake
Python
Power Apps
Power Automate
Salesforce CRM
SharePoint
Microsoft Fabric
Azure
Databricks
dbt
R / RStudio
Git / GitHub
Claude AI
DAX / M Query
REST APIs
Excel Advanced
Jira / Confluence
MarTech Stack

Get in touch to discuss anything.

Data Leader — Intake Agent Connects you directly

Opens the app with your message pre-filled — just hit send.