Experiments. Prototypes. Practical possibilities.
In the Lab
See what we’re building. We explore real problems through applied AI, research, and competitive challenges.
Full project walkthroughs
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Business research · WebMCP
AIZOYA Opportunity Intelligence
Submitted · The WebMCP ChallengeA submitted WebMCP prototype for discovering, comparing, and shortlisting opportunities through structured website tools. The public demo shows the original workflow; it does not establish live opportunity coverage or a production service.
Operations · Voice AI
AIZOYA Operator for Alexa+
Public demo · Synthetic prototypeA synthetic kitchen workflow that turns an inventory gap into a purchase plan, asks for human approval, and checks the evidence before marking work complete. The demo simulates Alexa+; it makes no real purchases or operational changes.
Hospitality · Referrals
Hospitality Referral Agent
Concept · Evidence review pendingA proposed workflow for organizing referrals, explaining priorities, and preparing follow-up drafts for review. The demonstration is withheld while evidence of its approval controls is reviewed.
Hospitality · Communications
CALLIVANTA
Public demoAn exploration of AI phone missions for hospitality operations, with human control over the work. Watch the public project demonstration.
Interactive experiments
Games in development
Games · Hospitality
Chaos Kitchen
Prototype · In developmentA cooking-game experiment built around ingredient choices, timed kitchen stations, and the pressure of service. We’re developing the experience; public access and paid features are not available yet.
Interested in playtesting or collaborating? Let’s talk.Built together · September 29, 2026
Collaborative hackathon work
ConnectMesh — Evidence Before Trust
Collaborative prototype · Media review pendingFranklyn Rosario, MBA-ITM, participated with fellow builders in this collaborative hackathon project exploring evidence review between AI agents on Flower SuperGrid. Credit belongs to the collaborating team; this is a shared project, not an exclusively owned AIZOYA product.
Completed research projects
Biohub · Kaggle · 2026
Tracking life with AI
Founder-reported completed entry · ResearchOur competition research explored detecting cells, linking their movement, and identifying divisions in 3D time-lapse microscopy of zebrafish development.
Illustrative research overview. No prize has been reported by the founder. It is not a diagnostic tool or a clinically validated product.
Read the video transcript
Life moves. One cell at a time. But following those cells through three-dimensional microscopy is a complex challenge.
Which cell is which? Where did it move? And how does its path connect across time?
We explored that challenge through Kaggle’s Biohub Cell Tracking During Development competition.
Our public competition score improved from a 0.827 baseline to a verified 0.953 submission.
Behind those numbers are experiments, difficult decisions, and lessons that shape what we build next.
This project shows how we approach research: define the challenge, test carefully, measure progress, and learn from the evidence.
Explore the project and what we learned.
The 0.953 public score came from a reproduction of a public competition notebook, not a claim of a novel model, accuracy percentage, final rank, or award.
Research in progress
Questions we’re exploring
RSNA · Knee abnormality detection
Exploring machine learning for recognizing abnormalities in knee imaging. Research prototype only; not clinically validated or intended for diagnosis.
ARC Prize · Reasoning & verification
Investigating whether testing candidate explanations can improve AI reasoning on unfamiliar puzzles. A research question, with results still being evaluated.
Competition on KaggleSelected public work
Evidence, one project at a time.
The demos above show work we have chosen to share. We’ll add competition results and project milestones here only when each item is verified and ready for public release.
Explore achievements & milestonesBuild with AIZOYA
Have a similar challenge?
Tell us what your team is trying to solve. Let’s explore what a useful first version could look like.
