Twenty years diagnosing the gaps between what SaaS companies promise and what customers actually experience. Now building AI-native tools to close those gaps faster.
See the toolsI don't just build AI tools. I have a structural framework for how organizations actually mature with AI — the AI Readiness-Depth Matrix. It separates organizational maturity from usage depth as two independent axes. Most companies and job descriptions conflate the two. That's why transformation efforts stall.
Twenty years running post-sale operations at growth-stage SaaS companies — healthcare, fintech, enterprise — gives me the execution lens that pure AI strategists lack. Strategy that can't be shipped isn't strategy. The tools below are the proof: structural thinking applied to real workflows, in production.
A customer intelligence platform that connects to your existing systems — CRM, support, product usage, billing — and applies a proprietary algorithm to monitor the leading indicators that predict retention, expansion, and churn before they show up in lagging metrics.
Built on the Trust → Prove → Grow framework: customers don't expand until they trust you, they don't trust you until you've proven value, and proving value requires measuring the right signals — not NPS scores and survey responses, but actual behavioral and operational indicators.
Most CS platforms track what already happened. Trust → Growth tells you what's about to happen — and what to do about it.
A career operating system with a unified Portal, an AI chief of staff called Della, and seven specialized applications that share data across every stage of the career lifecycle.
The Portal is the command center — phase-based dashboard (Land, Thrive, Advance), cross-app pipeline visualization, proactive AI insights from Della, and smart next-action recommendations driven by real activity data across all seven apps.
Della is the AI chief of staff embedded in every application. She reads your jobs, contacts, reflections, resumes, and skills — then tells you what to do next. Not a chatbot. A strategic partner who sees the whole board, spots patterns across apps, and drives action.
Institutional channel: Co-op mode enables structured workflows for university programs. Faculty get cohort dashboards with AI-powered student intelligence — early warnings, engagement correlations, alerts, and intervention suggestions. In pilot development with the University of Cincinnati.
Screenshots from both platforms — all in active use.
The Portal does AI-driven prioritization and action recommendation across seven data sources — ranking what matters now and telling you the specific next move. Della runs underneath it: cross-app pattern detection and proactive decision support, catching signals that don't show up in any single app. This is AI doing substantive analytical work across a full operating environment — not AI helping you draft an email.
AI-powered job scoring and pipeline tracker. Applies a structured, weighted framework to evaluate opportunities — so decisions are based on criteria, not gut feel.
AI-powered networking and outreach platform. Maps key contacts at target companies, sources personalized hooks for cold outreach, and generates tailored InMails — job-specific or cold.
Generates a complete interview prep guide from a job description and your background — tailored positioning, company intel, likely questions, and closing strategy.
Weekly reflections with AI accomplishment mining. Tracks skills, enforces cadence, and generates self-reviews from your reflection history.
Build, optimize, and tailor resumes with AI bullet rewriting. Imports accomplishments from Pulse. Multiple versions per target role.
Compare offers with real math, track certifications, build your promotion case, manage mentorship, and generate personal brand content.
Runs a structured diagnostic across Trust, Prove, and Grow dimensions to score customer health and surface the specific gaps blocking progression through each stage.
Continuous portfolio monitoring with automated risk flags and intervention triggers. Trust, realization, and growth signals are scored across your full book of business — then the system decides which accounts need action and surfaces the intervention. AI is running the monitoring loop and driving operational decisions, not assisting the CSM after the fact.
Most AI maturity models collapse organizational readiness and usage depth into a single line. They're not. They're two independent axes — and the gap between them is where most transformations stall.
A company can be high-readiness and low-depth (ready, but using AI as a glorified autocomplete) or low-readiness and high-depth (running AI the org can't actually support). Job descriptions conflate the two. Strategy decks conflate the two. That's why transformation efforts stall — you can't execute against a maturity model that's measuring the wrong thing.
Every tool I build started as a workflow problem I mapped on paper. AI accelerates execution — it doesn't replace the diagnostic work.
A single great interaction doesn't compound. I build for repeatability — frameworks and workflows that get better with use, not just tools that solve one problem once.
Every CareerStack module is something I've used on my own career challenges. If it doesn't hold up in practice, it doesn't ship.
Currently advising through Asendra Group and selectively exploring VP-level post-sale leadership roles at growth-stage healthcare SaaS companies. If that's relevant to you, or you just want to compare notes on CS operations and AI tooling — reach out.