I work with SaaS and technology teams to make AI reliable inside real workflows. The focus is practical execution: the right solution for your problem, built to fit your systems, your constraints, and the way your teams actually operate.
The value comes from designing the business system around that capability: workflows, ownership, evaluation, adoption, and governance that support consistent outcomes.
I start with your business reality, then architect the right solution that delivers durable results.
Many organizations have access to powerful AI tools, but the outcomes are inconsistent because the work is not designed as a system. I focus on building the workflow and operating model around the capability, so it performs reliably in day-to-day operations.
I work best with organizations that care about execution, quality, and repeatability. Most often, that means SaaS teams with high volume knowledge work and cross-functional coordination.
Standardize execution, accelerate analysis and documentation, and create reusable delivery intelligence that improves outcomes over time.
Improve response quality and consistency, strengthen knowledge systems, and reduce escalations through better signals and workflow design.
Build an AI operating model: intake, prioritization, evaluation, governance, and a cadence that makes adoption durable.
Improve CRM hygiene, enablement workflows, analysis, and customer-facing materials through repeatable AI-assisted systems.
Click into any package to see typical deliverables. If you are not sure where you fit, start with the audit.
AI Opportunity Assessment
Identify the highest-impact opportunities and the practical path to outcomes using your existing tools and workflows.
A focused diagnostic to pinpoint where AI can create measurable leverage, where the workflow breaks, and what needs to change for the outcome to stick. You leave with a prioritized plan your leaders can align on.
Teams that have AI access but need clarity on where to apply it and how to operationalize it.
AI Strategy Sprint
Move from ideas to an executable plan with clear architecture choices, sequencing, and ownership.
A deeper engagement that turns diagnostic insight into an actionable roadmap, including the solution patterns and operating model required to deliver and sustain outcomes.
Leadership teams that need alignment, clarity, and a plan that can be executed without constant rework.
Pilot Program
Take one high-priority use case to a working solution with measurement and adoption built in.
A guided build and launch for one use case that matters, designed to prove value and establish the operating habits required to scale. The goal is not a demo. The goal is a usable capability.
Teams ready to move from discussion to execution, but want a tight scope and measurable result.
Full Implementation Program
End-to-end delivery for multi-component solutions with governance, enablement, and durable ownership.
A full delivery engagement from roadmap through implementation and operationalization. Designed for teams that need measurable improvements across multiple workflows, not a single point solution.
Organizations ready to treat AI as an operating capability and invest in repeatability across teams.
Implementation Advisory Retainer
Fractional guidance while your team executes: decisions, quality control, stakeholder alignment, and momentum.
Ongoing advisory support for teams actively implementing AI initiatives. You get senior operating judgment, clear decisions, and practical guidance without adding complexity.
Teams already building, but need consistency, speed, and experienced oversight to keep quality high.
Custom Engagement
If your situation is unique, we scope a clear engagement around your outcomes, timeline, and internal capacity.
A tailored engagement when the packages above do not match what you need. We define a scope that is clear, outcome-focused, and aligned to your constraints before any work begins.
Complex situations with multiple stakeholders, multiple workflows, or unusual constraints.
The best use cases are the ones tied to real workflows where time, quality, consistency, and coordination matter.
Reduce analysis and interpretation time, accelerate documentation and customer communications, and improve delivery quality through repeatable systems.
Improve response consistency, strengthen knowledge operations, detect risk earlier, and reduce escalations through better workflow design.
Improve CRM hygiene, enablement workflows, competitive research, and proposal generation through structured AI-assisted systems.
Streamline documentation, extraction, reconciliation, and reporting with a focus on quality, auditability, and ownership.
Produce stronger analysis and market insight, repurpose content efficiently, and maintain voice consistency with clear guardrails.
Clarify ownership, define evaluation standards, establish governance that enables execution, and create a cadence that makes adoption durable.