JA Logic Labs leads software products from discovery through launch and continuous improvement—combining disciplined product strategy with applied AI, intelligent workflows, mobile, cloud, 3D, augmented reality, and emerging technologies where they create meaningful customer value.
JA Logic Labs is an independent software product studio that designs, builds, launches, and continuously improves specialized products across AI, mobile, B2B SaaS, augmented reality, 3D visualization, workflow automation, and predictive analytics.
Alongside our publicly released products, we pursue internal research, product incubation, technical prototypes, client collaborations, and new AI initiatives. The products and platforms featured on this site are a curated selection — spanning public products, products in development, and selected applied-AI work — drawn from a broader, continuously evolving body of work.
Every product starts with understanding a real customer problem and validating the opportunity before a line of code is written. From there the work is deliberate and cross-functional — defining measurable outcomes, aligning design, engineering, and data, launching intentionally, and improving continuously through user feedback and product analytics.
The outcome is software measured by adoption and impact rather than feature count — and that philosophy runs through every stage of our product development process.
A portfolio built end to end—from discovery through launch, monetization, and iteration.
Combined portfolio downloads
iOS • Android • macOS • Windows • Web
Monetized products — subscriptions and one-time purchases
Featured in JCK.
Built from product discovery through launch, monetization, measurement, and continuous iteration.
JA Logic Labs transforms complex professional processes into practical, accessible digital products across AI, mobile, 3D visualization, augmented reality, analytics, and workflow automation.
A selection of public products and initiatives illustrating how JA Logic Labs applies product strategy, AI, data, and software engineering across different problem spaces. These highlights are intentionally curated and do not represent the studio's complete portfolio, collaborations, or client engagements.
A mobile toolkit that unifies precious-metal calculations, costing, operational records, and CAD-related workflows for jewelry professionals.
PlatformsiOS · Android
A mobile 3D viewer for opening, inspecting, rendering, and sharing model files—turning technical assets into clear visual presentations.
PlatformsiOS · Android
A parametric ring-design platform that turns configurable parameters into three-dimensional concepts and production-oriented models.
PlatformsWeb
An applied-AI intelligence platform delivering market forecasts, London Fix analysis, Monthly Intelligence, confidence scoring, and downloadable executive reports for gold, silver, and platinum professionals.
PlatformsWeb
The work featured here represents a selected view of the JA Logic Labs portfolio. Additional work may include internal product incubation, applied-AI initiatives, technical prototypes, specialized workflow solutions, research efforts, collaborations, and client engagements that are not publicly showcased.
This ongoing work spans applied AI, workflow automation, B2B SaaS, augmented reality, predictive analytics, and other specialized software domains — an active pipeline that steadily becomes tomorrow's featured products.
Three complementary strengths. Product strategy and leadership remain the foundation; applied AI expands the technical breadth of that leadership; and end-to-end execution turns strategy into working products.
Understanding customers, identifying opportunities, defining products, prioritizing roadmaps, and leading products through their full lifecycle.
LLM-powered applications, hybrid AI and deterministic workflows, machine-learning systems, structured AI outputs, intelligent automation, agent-enabled workflows, evaluation, guardrails, and domain-specific intelligence.
Turning strategy into working products across web, mobile, cloud, APIs, data, 3D, AR, and specialized workflow software.
JA Logic Labs can determine both what should be built and why, and work deeply enough with technology to determine how it should be built.
Selected examples illustrating different ways JA Logic Labs applies AI, machine learning, algorithms, and deterministic software to real product problems.
LLM Interpretation + Deterministic Component Assembly
Natural-language design intent is interpreted by an LLM into structured design parameters, then handed to a deterministic Python workflow that composes predefined STL component templates into manufacturable geometry.
AI interprets intent while deterministic software handles geometry construction where precision and repeatability matter.
View Karats.AIParametric / Algorithmic Generation
A parametric generation system in which mathematical algorithms generate jewelry geometry from structured and natural-language inputs, producing STL output with visualization and AR capabilities.
Distinct from Karats.AI: RingOS is algorithm-driven parametric generation, not LLM-to-component assembly.
View RingOSMachine Learning + Structured AI Intelligence
An AI-powered precious-metals intelligence platform combining historical market data, machine-learning forecasts, AI Insights, London Fix analysis, Monthly Intelligence, market-regime analysis, confidence indicators, and executive PDF reporting.
Positioned as a decision-support and intelligence platform rather than a single prediction application.
View AUAGPT.ioGrowth Intelligence + Decision Support
A growth-intelligence platform exploring how product, audience, campaign, creative, and business signals can be transformed into structured analysis, recommendations, and decision support.
Demonstrates how AI can synthesize signals across multiple business functions rather than treating analytics, campaigns, and recommendations as disconnected workflows — a product in development, not a mature commercial release.
View StarGrowthSelected examples — not the complete scope of JA Logic Labs' applied-AI work.
Every product moves through the same evidence-driven path — a continuous loop rather than a one-way line.
Understand the user, workflow, market, business context, and underlying problem.
Test assumptions through research, prototypes, data, competitor analysis, and direct user feedback.
Translate validated needs into product strategy, requirements, priorities, architecture, and measurable outcomes.
Coordinate product, design, software engineering, data, AI, and quality efforts to deliver usable capabilities.
Prepare product positioning, distribution, monetization, operational readiness, analytics, and customer communication.
Evaluate adoption, engagement, quality, user feedback, product performance, and commercial results.
Continuously improve the product using evidence, evolving technology, and changing user needs.
Insights from each launch feed directly back into discovery.
A focused engineering loop applied to each AI initiative — from AI-fit assessment through architecture, evaluation, and guardrails to deployment and monitoring.
Determine whether AI meaningfully improves the user or business problem, and where deterministic software may be more appropriate.
Determine the appropriate combination of LLMs, ML models, structured data, APIs, algorithms, deterministic systems, and human workflows.
Validate feasibility and user value quickly.
Measure output quality, reliability, failure modes, and usefulness against defined criteria.
Apply structured outputs, validation, business rules, bounded actions, human review, and failure handling where appropriate.
Integrate the AI capability into the real product workflow.
Measure product outcomes, system behavior, quality, adoption, and opportunities for improvement.
AI engineering operates within our broader product-development discipline — not separately from it.
See our product lifecycleEditorial coverage, awards and recognition highlighting selected milestones across the JA Logic Labs portfolio.
JCK Magazine featured Jewelers' Assist and highlighted how JA Logic Labs is helping modernize jewelry production through software, visualization, workflow automation, and digital tools.
Lead Product Manager
Jack Hillel leads product strategy and execution across selected JA Logic Labs products and initiatives, guiding opportunities from customer discovery and product definition through technical delivery, launch, commercialization, measurement, and continuous improvement.
His work spans applied AI, technical product management, B2B SaaS, mobile software, predictive intelligence, 3D, and augmented-reality products, with a focus on translating complex domain workflows into useful, scalable software.
Across selected public portfolio highlights, that work includes AI and machine-learning intelligence platforms, LLM-assisted deterministic workflows, parametric product-generation systems, professional mobile software, and subscription products — contributing to products that have surpassed 100K+ combined downloads.
Technology choices vary by product and problem. This represents selected technologies and technical capabilities used across the JA Logic Labs portfolio — not an exhaustive stack.
Contact
JA Logic Labs welcomes conversations with recruiters, founders, hiring managers, product teams, and potential collaborators exploring specialized software and AI opportunities.
Send a short note about the role, product, or collaboration you have in mind and we'll get back to you. Include your organization and a topic so we can route your message.