Project portfolio
Software, AI, and operator systems built from real business pressure.
This portfolio is not a gallery of fake app ideas. It documents active build lanes, internal systems, prototypes, and product architecture connected to the Stretch ecosystem, my personal site rebuild, and applied AI development.
Live dev buildNext.js portfolio rebuild
ross-stretch.com Rebuild
A controlled rebuild of my personal site away from WordPress into a custom Next.js publishing and portfolio system.
Problem
The legacy WordPress archive carried old AI-era content, inconsistent quality, and limited control over SEO, structure, redirects, and portfolio positioning.
Outcome
A live SSL-secured dev deployment with Docker runtime, NGINX routing, markdown-backed article rendering, and a clean first pillar article route.
Next.jsTypeScriptDockerNGINXCertbotMarkdown content
Proof points
- dev.ross-stretch.com deployed over HTTPS
- First pillar article route rendered from markdown
- Reusable runtime verification script committed
- Production DNS intentionally held until QA and redirects are ready
Internal platform laneAI systems / model factory
StretchGPT / Foundry
A sovereign AI product lane focused on applied language-model workflows, evaluation, dataset direction, image-generation planning, and multi-worker model-factory architecture.
Problem
Most AI usage stays trapped at prompt level. The goal is to turn AI into a governed software system with workflows, datasets, evaluations, versioning, and product surfaces.
Outcome
Architecture direction for internal admin tooling, future client-facing StretchGPT access, hybrid compute, and specialized model/product lanes.
PythonTypeScriptNodeDockerAI APIsGPU planningEvaluation workflows
Proof points
- Foundry architecture documentation
- Worker-lane planning
- Algorithm and learning-system direction
- Hybrid compute direction using cloud plus local GPU capacity
Prototype laneBrand intelligence system
StretchBAS Lite
A brand audit and business analysis system designed to evaluate positioning, audience clarity, offers, messaging, and campaign readiness.
Problem
Small businesses often buy websites, ads, and content before their offer, message, and customer logic are clear enough to convert.
Outcome
A structured AI-assisted audit concept that can eventually feed reports, recommendations, content plans, and client-facing advisory tools.
AI workflowsBrand strategyStructured scoringReport generationAdmin app planning
Proof points
- Named product lane
- Scoped away from crawler/Search concerns
- Designed for internal use first
- Future white-label/client-dashboard path identified
Architecture laneCrawler / SEO intelligence
StretchSearch Lite
A focused web intelligence system for authorized crawling, SEO extraction, page indexing, content mapping, and business research.
Problem
Brand, SEO, content, and audit systems need reliable source intelligence instead of disconnected manual research.
Outcome
A separate product lane from StretchBAS, with crawler, index, SEO intelligence, and future integrations across the Stretch ecosystem.
Python crawlerPostgreSQLSEO extractionEntity indexingAI summaries
Proof points
- Separated from StretchBAS to keep each app focused
- MVP crawler/index scope defined
- Designed to feed audits, support docs, content systems, and StretchGPT
Concept buildAgency operations tooling
Agency Ops Agent
A software assistant concept for agency intake, delivery, follow-up, project tracking, reporting, and client execution workflows.
Problem
Agency work breaks down when leads, proposals, delivery tasks, assets, client context, and follow-up live in separate systems.
Outcome
A direction for internal tooling that connects sales, delivery, documentation, support, learning, and reporting into a cleaner operator dashboard.
Workflow designCRM conceptsTask systemsAI assistanceAdmin dashboard UX
Proof points
- Aligned with StretchCRM and StretchProjects direction
- Designed around operator execution instead of generic task lists
- Future client-dashboard/product path possible
Planned utilityAI testing / evaluation
AI Evaluation Harness
A repeatable testing layer for comparing prompts, model outputs, workflows, extraction quality, and AI-assisted software behavior.
Problem
AI output is easy to generate and hard to trust without repeatable evaluation, comparison, and regression checks.
Outcome
A practical evaluation utility planned for AI product development, content pipelines, data extraction, and internal StretchGPT governance.
Prompt testingOutput scoringRegression checksDataset fixturesModel comparison
Proof points
- Tied to StretchGPT Foundry direction
- Useful across BAS, Search, Learn, and content systems
- Designed as infrastructure, not a one-off script