All work

Decision IntelligenceCase study

SAS Decision Builder

Took SAS's first cloud-native AI decisioning SaaS from concept to Microsoft Marketplace GA in under 12 months. LLM-powered decision explainability, pre-production validation, and Microsoft co-sell, all owned end-to-end.

An AI-native decision intelligence SaaS on Microsoft Fabric, taken from concept to Microsoft Marketplace GA in under twelve months under single-threaded PM ownership. Pay-as-you-go pricing. Owned product, GTM, partner enablement, and Microsoft co-sell end-to-end during a fund-or-kill investment window.

What the product does

Decision Builder is a decision orchestration layer where customers compose decisions from rules, custom Python, ML models (Azure ML, MLflow), and recursive sub-decisions in a visual decision flow UI. It runs on Microsoft Fabric and ships with LLM-powered decision explainability that generates plain-English rationale and supporting evidence for every decision a deployed flow produces, addressing a regulated-industry requirement legacy decisioning platforms do not meet.

What I owned

  • Product strategy and roadmap, end-to-end, without a partner manager, dedicated PMM, or analyst relations function.
  • The decision orchestration model itself: which decision primitives to compose with, how recursive sub-decisions flow, where rules versus models versus LLMs belong.
  • LLM-powered decision explainability as a first-class feature, not a side capability.
  • Pre-production decision validation as the competitive wedge: simulating decisions against historical data and surfacing edge cases before deployment. Primary sales hook in regulated industries.
  • Microsoft Marketplace launch: value metric, free-tier limits, product-qualified-lead criteria bridging self-serve activation to enterprise co-sell pipeline.
  • The Microsoft co-sell motion end-to-end. Initiated co-sell pursuits and built the SI/reseller partner enablement program from scratch.
  • The fund-or-kill business case for leadership, which secured continued investment.

Customer outcomes

Converted design partners and paying customers across banking, insurance, and public sector use cases (credit risk, underwriting, emergency-call triage) with named references in regulated industries.

Substituted for missing functions

With no dedicated product marketing, ran 15+ customer discovery interviews, produced 15+ YouTube product demos, 7+ long-form blog posts, and multiple webinars in support of the launch.

What this demonstrates

AI-native enterprise SaaS leadership. End-to-end PM execution under fund-or-kill pressure. LLM integration in production grounded in real regulated-industry constraints. Microsoft ISV partner motion run without a partner manager. Cradle-to-GTM ownership including PMM-equivalent content.