Core Identity

Builder of unified partner operating systems

The consistent pattern across roles is not title inflation. It is individual ownership of complex systems while coordinating cross-functional teams around CRM, ERP, analytics, partner workflows, and revenue operations.

Deep strengths: Salesforce architecture, system integration, analytics, partner lifecycle management, operational governance, and the business judgment to understand the financial impact behind technical choices.

AI Focus

For the last two years, AI has been the active build layer: workflow automation, orchestration, reporting, forecasting insight, RAG architectures, and systems that interpret data and trigger actions automatically.

  • n8n and low-code orchestration patterns
  • AI-assisted reporting and pipeline risk surfacing
  • Vector databases and RAG for retrieval and decision support
  • Automation across CRM, partner systems, and reporting
AVST16 years building end-to-end partner ecosystem
CPQ Scale$100M+ annual quote volume
XMedius1,000+ partners, approvals down 60%
OpenTextForecasting accuracy improved 60%
CognigyForecasting accuracy doubled

The Crown Jewel

AVST Built as a Full PRM Ecosystem Inside Salesforce

Over sixteen years, the AVST platform became a cradle-to-grave partner and revenue operating system, built personally inside Salesforce before the market had standardized PRM platforms.

Front DoorPartner portal, communications, enablement
PipelineDeal registration, forecasting, co-sell visibility
CommercialCPQ, discounts, pricing, margin governance
Control LayerCRM, ERP integration, dashboards, entitlements, renewals
Every component companies expect from a modern PRM platform now, partner portal, deal registration, forecasting, CPQ, analytics, communications, governance, I had already built inside Salesforce.

Modern Stack View

CRM + PRM + Ecosystem Discovery Layer

Today’s partner stack is familiar: Salesforce as system of record, PRM platforms like Impartner or Mindmatrix for lifecycle management, and discovery platforms like Crossbeam or PartnerTap for overlap and co-sell intelligence.

  • PRM layer: onboarding, deal reg, training, tiers, MDF, reporting.
  • Ecosystem layer: secure CRM sharing, overlap detection, co-sell discovery, influenced revenue attribution.
  • Salesforce direction: Partner Cloud is converging toward the same unified operating model I have spent much of my career building.
AI is now the behavior layer: opportunity discovery, partner scoring, forecasting, matching, routing, and lifecycle triggers.

Career Arc After AVST

XMedius Governed partner workflows, consolidated CRM and CPQ, cut approval times 60 percent.
OpenText Global Salesforce and ERP integration, CPQ automation, forecasting accuracy up 60 percent.
Cognigy Unified pipeline with NetSuite financials, built reporting trusted across regions, doubled forecasting accuracy.
Trusted Tech CRM architecture, pipeline analytics, Chargebee, Shopify, Salesforce integrations, CAB governance.
Consulting AI-assisted workflows, orchestration pipelines, diagnostics across forecasting, CRM, reporting, and GTM systems.

PRM Bridge

I have not implemented Impartner or Allbound off the shelf, but the architecture behind those systems is exactly what I built from scratch inside Salesforce.

  • Direct Channeltivity and partner workflow exposure.
  • Enterprise application depth across Salesforce, HubSpot, Service Cloud, Marketing Cloud, Communities.
  • The platform learning curve is weeks. The operational depth behind it takes years.

Why This Role Fits

This role is asking for someone who can own the full lifecycle of partner systems transformation, strategy through execution, while understanding both the systems and the business.

  • Partner ecosystem architecture
  • Salesforce systems integration
  • Partner analytics and forecasting
  • AI-enabled automation
  • Revenue operations infrastructure
You want someone in the foxhole who will not leave the mission on the beach. That is how I operate.

Close

What I built at AVST became the foundation for everything since. Each role added more scale, more complexity, and now AI is the next layer changing how operational systems behave.

Best ending: NICE operates one of the largest partner ecosystems in the industry. Building the operating system behind that ecosystem is exactly the kind of mission I enjoy.