Offer
Custom software systems
I design and ship software that matches the way your business actually operates instead of forcing you into generic tools.
`signal.aiwithken.com` is the public front door for my consulting work and the live research lab behind my stock-market data warehouse. On one side: product and platform delivery. On the other: transparent market research, model cards, and pre-market data storytelling.
Current focus
Consulting lane
Custom apps, data pipelines, analytics delivery, and AI product work for businesses that need something beyond templates.
Creator lane
An explainable research hub built on my medallion warehouse, with market context, stock pages, macro dashboards, and model cards.
Cadence
Overnight / pre-market refresh
Posture
Educational research, not advisory language
What I do
The work spans product delivery, warehouse design, reporting, and AI implementation. The common thread is that the output has to be usable by real people, not just technically interesting.
Offer
I design and ship software that matches the way your business actually operates instead of forcing you into generic tools.
Offer
I build pipelines, warehouses, and reporting layers that turn messy source systems into decision-ready data products.
Offer
I translate real business and market questions into model-ready datasets, explainable features, and production delivery paths.
Offer
I stay close to the systems after launch, harden the runtime, and keep the product usable as the data and user load grow.
Featured client build
Create an ordering flow that feels custom, branded, and easy for guests to use without collapsing into a generic template.
A live ordering surface with clear menu structure, confident visual branding, and a product feel that supports the business instead of fighting it.
Client type
Restaurant / hospitality
Role
Product design, frontend engineering, backend integration, and polish
What I handled
The Lab
The Lab turns the warehouse into market explainers, stock breakdowns, macro context, and transparent model cards. It is designed for authority and education first, with room to scale toward broader coverage and richer model outputs over time.
Warehouse-native screening
Sort the covered universe by technical context, sentiment, and data quality instead of reading raw tables.
Per-company breakdowns
Open a covered stock and read the price trend, fundamentals, sentiment context, macro backdrop, and data health in one place.
Context before the open
Track the macro series powering the warehouse and the regime flags derived from the latest transforms.
Trust and observability
See what the warehouse currently covers, the latest run metadata, and whether the data is healthy enough to publish.
Transparent research systems
Review what each model or scoring surface does, how often it refreshes, and what caveats come with it.
Educational research only. Nothing on this site is personalized investment advice or a guarantee of future performance.
Background
Master’s in Data Science
U.S. Army Information Technology Specialist background
Hands-on database, analytics, and application delivery experience
My work lives at the intersection of product delivery, data engineering, and AI implementation. I like building systems where the warehouse, the application layer, and the user-facing story all fit together cleanly.
The stock lab on this site is not a side gimmick. It is a public proof surface for how I think: source data, layer contracts, quality gates, explainable outputs, and honest caveats about what the system can and cannot claim.
That same discipline is what I bring into client work. Whether the project is a restaurant ordering experience, an internal analytics product, or a warehouse-backed AI feature, the goal is the same: ship something real, keep it understandable, and make the system reliable enough to trust.
Next step
The site now does both jobs on purpose: consulting lead generation and transparent public research. Reach out if you want custom software, data infrastructure, or AI product work. Follow the Lab if you want to see how I think in production.