I'm Mike Pace. For a decade I helped enterprise customers succeed with complex security technology — as an engineer, then as the person who turned adoption barriers into renewals. Now I'm pursuing my MS in AI and putting it to work every day.
Years in Customer Success & engineering
+ Security+, CySA+, SSCP & CyberOps
Kennesaw State University · 2027
High-value security customers & partners
My career started deep in the technical trenches — standing up complex security deployments, supporting the behavioral-analytics platforms that detect advanced threats, and keeping mission-critical systems stable for some of the most demanding enterprise customers in the world.
But the work I loved most was never just the technology. It was the moment a customer went from struggling with a tool to trusting it to protect their business. That's what pulled me into Customer Success: turning adoption barriers into confident, renewing, thriving customers.
Since 2025 I've made a deliberate bet on what comes next: I stepped into my Master's in Artificial Intelligence full-tilt and rebuilt how I work around AI — researching, drafting, analyzing, and automating so I can spend more time on the human part of the job. It's been a season of sharpening, not sitting still. This portfolio is a window into that practice.
"The best customer success isn't about the product. It's about helping people realize the outcome they were promised — and AI lets me do that faster, and more thoughtfully, than ever."
These aren't hypotheticals — they're how I've spent the past year using AI to build and run real businesses: writing software, modeling finances, automating operations, and making sense of messy information. I'm happy to walk you through any of them.
I run a small Turo car-sharing fleet, and I built the software that runs it. It started as a single-file browser tool tracking one fleet's unit economics; today it's Curblane — a multi-tenant SaaS product, deployed and functional, with authentication, a tiered subscription model, per-vehicle profit-and-loss reporting, a parking break-even optimizer, and product analytics. It's in pre-launch with a founding-operator waitlist. Its core metric is realized daily rate against market benchmark, so an operator can see where revenue is actually leaking rather than just what a booking grossed.
My digital-products shop runs on an AI automation I designed: every week it researches trends, builds a batch of new spreadsheet products on a consistent design system, quality-checks the formulas, and writes the listings — a product line that largely runs itself.
I built AI models that pull live vehicle listings from multiple marketplaces and rank every purchase candidate by projected cash flow — turning a gut-feel buying decision into a data-backed one, with depreciation, financing, and utilization all modeled.
I use AI to build the kind of analysis that used to require a consultant: multi-year P&L models with scenario sensitivity, unit economics, and a full growth plan — the financial backbone behind the businesses I run.
I used AI to work through a large, unstructured set of records and correspondence spanning several years — extracting and cross-referencing facts, reconstructing a precise chronological timeline, surfacing inconsistencies, and producing a clear, verifiable evidence summary for a high-stakes review. A study in turning overwhelming information into a defensible narrative.
AI is woven through my daily work — research, drafting, analysis, and automating busywork so I can focus on people and outcomes. Case in point: this portfolio and my résumé were built collaboratively with an AI agent, working from my real projects.
A deliberate pivot into AI. I designed, built, and deployed Curblane, a multi-tenant SaaS platform for vehicle-sharing fleet operators — authentication, a tiered subscription model, per-vehicle P&L, and product analytics — now in pre-launch with a founding-operator waitlist. Alongside it I operate a six-vehicle car-sharing fleet in Atlanta, handling the full guest lifecycle and carrying a collision claim from date of loss through independent inspection to funded settlement in two days. I also built the 24-month financial model that sets the acquisition criteria for every vehicle I add, and run an automated digital-products shop. Pursuing my MS in Artificial Intelligence in parallel.
Helped build a 4-person High-Value Recovery team from the ground up — interviewing candidates and, each quarter, segmenting the Salesforce account base by renewal-risk criteria to target at-risk, unassigned customers. Renewal rates across those targeted accounts moved into the low 90s within six months and held. Authored the team's onboarding playbook and recovered stranded accounts — onboarding a brand-new admin at a major retailer through a dual-domain merger deployment in under two weeks, then securing training credits to make them self-sufficient. Served as enablement lead for the Cisco XDR launch, running train-the-trainer for 13 partner sellers across 3 strategic partners, and managed adoption, success plans, and QBRs across a scaled book of 72 accounts ($20K–$75K ARR).
The dedicated 24/7 engineer trusted with the network-security-monitoring backbone of two of Cisco's most demanding accounts — a top-3 U.S. bank and a global asset manager — on Cisco Secure Network Analytics and Secure Cloud Analytics. When a performance crisis threatened a multi-year contract, I pushed for and helped lead an emergency cross-functional on-site and drove an overnight hotpatch into production, keeping the relationship intact. Delivered the white-glove support behind the bank's premium tier — knowledge-transfer sessions and overnight upgrade windows — and assisted the SE and technical architect on their multi-site hardware deployment (data migration, data load analysis for load balancing, and troubleshooting).
Troubleshot escalated application and networking issues, coordinated delivery of software fixes and customizations, and performed in-depth technical analysis of complex escalations.
A blend of customer success leadership, deep technical fluency, and a growing command of applied AI.
I'm actively exploring Customer Success roles at AI/ML, SaaS, and security-focused companies — places where the customer's outcome depends on getting complex technology to actually land. If that's the team you're building, let's talk.