Learning ecosystems, operational infrastructure, AI workflows, and knowledge systems — designed to scale, built to last.
Custom Copilot agent trained on Absorb documentation for real-time architecture decisions without vendor escalation.
AI workflow that outputs complete quiz questions with custom per-answer feedback at ~90% accuracy before SME review.
Scribe AI-based documentation infrastructure across Proofpoint and Moore — from enrollment workflows to onboarding SOPs.
Three organizations, three different scales, one consistent pattern — building systems that work better after I leave than before I arrived.
Translating executive vision into scalable operational infrastructure — Moore’s first enterprise learning ecosystem, built from zero.
Moore had no centralized enterprise learning ecosystem. Knowledge transfer, onboarding, content governance, and learning visibility were fragmented across teams.
Built the company’s first enterprise learning ecosystem: LMS implementation, governance workflows, content intake, contributor standards, reporting dashboards, onboarding infrastructure, and AI-assisted content workflows.
Created a scalable learning foundation supporting 1,400+ active learners, 15,000+ completions, a 40-credit enterprise learning model, 79 contributing SMEs and growing, executive reporting visibility, and future expansion toward full organizational reach.
Moore is a large professional services organization operating across multiple business units. When I joined in April 2025, it did not have a centralized enterprise learning ecosystem. Knowledge transfer was fragmented. Onboarding was inconsistent. There was no shared infrastructure for how employees learned, developed, or accessed training across the organization.
There was a vision for one. But no platform, no governance, no operational infrastructure, and no clear path from idea to execution. My first day, I was pulled directly into LMS evaluation. That set the pace for everything that followed.
I evaluated five LMS platforms against a custom requirements matrix, scoring each on functionality, scalability, integration capability, and organizational fit. Based on that evaluation, I recommended Absorb LMS, which became the platform of record.
The LMS was only part of the work. The ecosystem needed a complete operational foundation. I built the systems that allowed Moore to Learn to function at scale:
Partnering with HR and Communications, I helped operationalize Moore’s executive vision for a structured onboarding program, turning it from concept into a functioning system.
I built and maintain executive-facing dashboards in Absorb Analyze, giving leadership real-time visibility into platform adoption, engagement trends, course completion rates, content performance, and operational health metrics.
79% participation from a standing start is a meaningful adoption signal. A 4.36 average course rating reflects not just completions but content quality that meets expectations. The 40-credit enterprise learning model introduced a clearer standard for annual participation and gave the program a more durable operating rhythm.
The governance and workflow infrastructure made it possible for 79 contributing subject matter experts and growing to participate across the organization, which is what makes it scalable.
Most of the systems I built did not exist before I built them. That is not a footnote. It is the point.
Training operations at enterprise scale — 90,000+ learners, an LMS migration, AI chatbot knowledge architecture, and the documentation infrastructure that kept everything running.
Training operations served a large external learner population, but support workflows, documentation, migration communications, and knowledge access needed stronger operating infrastructure.
Built process documentation, support workflows, chatbot knowledge architecture, migration communications, rebrand FAQs, Salesforce reporting support, and certification operations resources.
Supported 90,000+ learners, resolved 810+ Salesforce cases, standardized support workflows, reduced repeated knowledge gaps, and contributed to renewal and certification program operations.
Proofpoint’s Cybersecurity Academy served enterprise customers, channel partners, and internal teams across cybersecurity certifications, instructor-led training, and self-paced learning.
First point of contact for daily stakeholder inquiries across training, enrollment, certification support, and platform access. Over 14 months: 810+ Salesforce cases resolved.
Contributed to platform testing, configuration, and learner communications for a migration affecting 90,000+ users globally.
Developed the knowledge base that powered an internal AI chatbot: conversation flows, FAQ scripts, and support use cases that formed the chatbot’s operational core.
Built cross-functional process guides covering workflows across support, training delivery, and customer success.
“Sara had put together extensive documentation — she was usually one step ahead of every ask.”
— Kate O’Keefe, Cybersecurity Academy Community Manager, ProofpointCo-led communication strategy reaching customers, partners, and internal teams. Wrote segmented email campaigns and authored the FAQ sheet distributed across internal channels.
Operating at this scope as an intern required treating the role as a full operational function, not a support position.
Built a scalable internal resource system despite limited tooling and loosely defined requirements — creating structure before formal ownership existed.
Teams were wasting time searching for scattered resources across bookmarks, Slack threads, emails, and tribal knowledge.
Built a centralized resource library with role-based organization, maintenance workflows, audit tracking, and stale-link governance.
Improved access to institutional knowledge, supported faster onboarding and proposal prep, and reduced duplicate searching in a fast-moving partnership environment.
The Client Partnerships team operated in a fast-moving environment with hundreds of tools, portals, reports, and links spread across individual bookmarks, Slack messages, and whoever happened to know where something lived. The work did not need another static spreadsheet. It needed resource infrastructure.
I built a centralized resource library in Google Sheets: 350+ curated links, role-based filters, automated sorting through App Scripts, audit tracking with review dates, and maintenance workflows for outdated links.
The system reduced information friction for client teams and improved speed-to-execution by making resources easier to find, easier to maintain, and easier to use during onboarding and proposal preparation.
The Link Library became an onboarding asset for new team members and remained in active use more than a year after I built it. Its value was not only the number of resources centralized. The value was the governance layer: clear structure, ongoing maintenance, and a single place to find institutional knowledge.
Built a scalable internal resource system despite limited tooling and loosely defined requirements — creating structure before formal ownership existed.
A research project designed to expand Ibotta’s reach and better serve Hispanic and Spanish-speaking consumers through multi-language app support and targeted market visibility.
Spanish-speaking consumers showed signs of demand, but Ibotta needed a clearer business case for language support, market visibility, and user growth opportunities.
Delivered a research deck combining market demand, user behavior insights, competitor review, scraped social comments, and recommendations for Spanish-language app and campaign strategy.
Provided actionable insights that supported Ibotta’s focus on the Hispanic and Spanish-speaking market and informed Spanish-language marketing initiatives.
Ibotta had an opportunity to better serve Hispanic and Spanish-speaking consumers, but the work required more than a general recommendation. The business case needed evidence: market demand, consumer behavior, user friction, and practical visibility channels.
I collaborated with D2C Español, Market Research, Consumer Insights, and UX to explore user demand and feasibility for multi-language app support. I used Octoparse to scrape comments from YouTube and TikTok, exported the data into Excel, and used translation formulas to analyze Spanish-language feedback at scale.
As part of the pitch, I also recommended evaluating emerging AI translation tools to streamline the process of implementing multi-language app support, with subject matter experts reviewing translated content for accuracy, tone, and cultural fit before release.
I also developed a case study around a bilingual TikTok creator whose tutorials helped Spanish-only speakers navigate Ibotta while the app was still English-only. One creator video generated 3,000 organic referrals, demonstrating demand that was already finding its own workaround.
The research supported recommendations for Spanish-language app support, influencer opportunities, and targeted visibility channels. I also researched high-impact podcast advertising opportunities and recommended Yo Quiero Dinero, which was selected for a paid feature to increase Ibotta’s visibility with Spanish-speaking users. The initiative contributed to Ibotta’s broader Spanish-speaking market focus and informed two Spanish-language marketing initiatives, including Seguro que lloverá and Muestra gratis.
This project was not just research. It was pattern recognition: finding user demand before the product fully supported it, then translating that signal into a business case leadership could act on.
Discrete systems, AI workflows, and operational tools built across roles — each solving a real problem.
Hundreds of team resources scattered across bookmarks, Slack threads, and tribal knowledge.
A self-maintaining resource system in Google Sheets: 350+ curated links with automated sorting, role-based filters, audit tracking, and alerts for outdated links.
Spanish-speaking users showed demand, but the business case for language support and targeted visibility needed stronger evidence.
A cross-functional research project using market analysis, consumer insights, scraped social comments, and a creator case study to build recommendations for Spanish-language app and campaign strategy.
Turning raw SME knowledge into structured course assets was time-intensive and inconsistent.
An AI-assisted workflow that transforms raw SME material into structured course outputs: outlines, objectives, and early drafts.
Building quizzes with meaningful custom-tailored feedback for every answer choice was slow and inconsistent.
An AI workflow that outputs complete quiz questions with custom feedback per answer choice, formatted for SME review.
Internal facilitators received inconsistent, vague feedback after sessions.
A Claude workflow that evaluates presentation recordings and transcripts against a structured coaching framework.
LMS architecture decisions and troubleshooting required vendor escalation or manual sandboxing.
A custom Microsoft Copilot agent trained on Absorb LMS documentation for troubleshooting and architecture decisions.
Operational workflows across training, onboarding, and platform administration were undocumented.
Scribe AI-based documentation systems at Proofpoint and Moore for enrollment workflows, onboarding SOPs, and platform operations.
Selecting an enterprise LMS without a structured framework risks choosing based on demos instead of organizational fit.
A custom requirements matrix scoring five LMS platforms across functionality, scalability, integration capability, and fit.
Leadership had limited real-time visibility into adoption, learner behavior, or content performance.
Executive-facing dashboards in Absorb Analyze for adoption trends, completion rates, content ratings, and engagement patterns.
Course knowledge, learner feedback, content assets, reporting data, and contributor information lived across disconnected LMS exports, SharePoint folders, files, and manual workflows.
A structured SharePoint-based knowledge repository designed to support AI-assisted search, course maintenance, evaluation analysis, content governance, and future Copilot agent workflows.
Course feedback was difficult to interpret at scale because raw evaluation data did not automatically translate into trend visibility, quality signals, or content improvement priorities.
A repeatable reporting workflow that turns course evaluation data into structured HTML reports with historical feedback, comparative trends, rating summaries, response-volume context, and improvement signals.
Content intake and external learning credit submissions arrived through informal channels with limited visibility.
Workflow redesigns using Jira, Microsoft Forms, and PowerAutomate to improve intake organization, tracking, and approval throughput.
At Moore, there was no enterprise learning ecosystem — I built one. At Proofpoint, the documentation that new team members relied on did not exist yet — I wrote it before anyone asked. At Ibotta, there was no centralized resource system — I built one that still runs itself more than a year after I left.
The pattern is not coincidence. I am drawn to the ambiguous early stage: when there is executive vision but no operational foundation, when the problem is clear but the system to solve it has not been designed yet.
My background spans learning operations, knowledge systems, AI workflow design, and cross-functional program management. I have implemented enterprise LMS platforms, designed governance frameworks, built AI-assisted content pipelines, and run training operations at the scale of 90,000+ users.
I am currently the Learning & Development Program Manager at Moore, leading the continued expansion of Moore to Learn — the enterprise learning ecosystem I helped build from zero.
Outside of work, I enjoy reading, traveling, and trying new things that usually become projects. I think the best systems are the ones that feel obvious in hindsight.
Colleagues, managers, and cross-functional partners across Moore, Proofpoint, Ibotta, and beyond.
Whether you’re exploring a role, a collaboration, or just want to talk systems and learning infrastructure — reach out directly.