FrankieVerse by Good Tattoo AI

Understand what your animals can’t tell you

Good Tattoo AI is building FrankieVerse to reveal meaningful shifts in animal behavior, routine, and wellbeing — no collar required, no camera required, nothing they wear.

FrankieVerse is being designed as an ambient sensing and behavioral insight system for the spaces animals already live in.

Privacy-first sensing

No cameras required

Routine-based insights

Patent-pending behavioral intelligence platform

Discuss a pilot

Gentle technology for stronger bonds.

The Problem

Animals can't tell us when something is wrong

Subtle changes in routine, movement, or environment are easy to miss. By the time we notice, a small issue may have already become a larger one.

Nonverbal by nature

Animals communicate through behavior, not words. Discomfort, stress, routine disruption, or inter-animal conflict often go unrecognized until they escalate into visible problems.

Cameras feel invasive

Pointing cameras at pets, caregivers, or shared spaces creates a surveillance environment that feels unnatural for everyone involved. Privacy shouldn't be the price of insight.

Collars and wearables are limited

Constant-wear collars, tags, and trackers are impractical for many animals and situations. They capture narrow data, require charging, and don't reflect the full environmental context an animal lives in.

Behavior speaks. FrankieVerse translates.

FrankieVerse app concept showing a new stress pattern with high barking correlation.

Concept preview

FrankieVerse is being designed to surface patterns that may otherwise be easy to miss — changes in routine, movement, location, and ambient context that could point to shifts in wellbeing. For example: less morning activity, fewer food-area visits, and more window-watching could suggest a possible routine change when correlated with nearby barking activity.

How It Works

Sense → Infer → Decide → Respond → Learn

A continuous pipeline that builds understanding over time while respecting privacy at every layer.

Sense

Detect movement, routine patterns, and environmental context through ambient signals—without requiring cameras or body-worn sensors.

Infer

Model behavioral context—distinguishing normal variation from meaningful shifts in activity, presence, or routine.

Decide

Determine whether something needs attention, routing, escalation, environmental adjustment, or continued observation based on learned thresholds and context.

Respond

Route an alert, flag a pattern for review, or coordinate an adaptive response across connected devices, always with human judgment in the loop.

Learn

Build individual behavioral profiles over time. Each animal, each home, each environment is unique. The system gets smarter with context.

Use Cases

Where understanding matters most

FrankieVerse applies wherever animals live, move, and interact—from private homes to professional animal care settings.

Pets at home

Understand your animal's daily rhythms. Notice when eating, elimination, sleep, or activity patterns shift in ways that may warrant attention—without surveilling your own home.

Multi-pet households

In homes with multiple animals, resource access, territory, and inter-pet dynamics create complexity. Ambient sensing can help identify tension or exclusion before it escalates.

Boarding, shelter, and veterinary

Professional animal care settings benefit from behavioral insight across multi-animal environments, cages, kennels, and shared spaces. Detect stress, illness, or routine disruption earlier across many animals at once, and surface patterns that inform care workflows across staff and shifts.

Routine deviation and caregiver review

When a pet sitter, family member, or staff member takes over care, context is often lost. Ambient behavioral profiles preserve institutional knowledge about what normal looks like for each animal.

Privacy & Trust

Designed for the home, not the surveillance room

Privacy is not a feature bolt-on—it is an architectural commitment. FrankieVerse is built on a privacy-first foundation from Good Tattoo AI, designed around dignity, trust, and minimal data collection.

Privacy-first architecture

Behavioral inference happens with the minimal data necessary. No raw video, no constant audio streaming, no always-on connectivity requirements.

Local-first where possible

Processing that can happen at the edge stays at the edge. Sensitive behavioral data need not leave the environment it describes unless you choose to share it.

Human-sensitive data suppressed

Where human and animal data overlap, the system is designed to minimize, anonymize, or suppress human-identifiable information. Animal insight should not require compromising human privacy.

The name, and where it began

Good Tattoo was the name of co-founder Paul Finn’s great-great-grandmother. She was Assiniboine, part of the Nakoda people of the northern Plains, and was born in a tipi in what is now northern Montana.

For Paul, the name carries family, memory, and a belief that animals are not background characters in human life. They have presence, spirit, patterns, needs, and signals we too often miss.

That belief became personal with Frankie — a cat whose changing behavior raised a larger question: what are nonverbal beings trying to tell us when they cannot explain why some days are harder than others?

Good Tattoo AI was founded around a shared conviction: nonverbal behavior deserves better interpretation, and beings who cannot explain themselves in human language deserve a better way to be heard.

The bigger vision

FrankieVerse is the first product from Good Tattoo AI, built around the idea that behavior is communication. The same platform architecture may extend over time into care environments, adaptive homes, robotics, and nonverbal communication.

Explore the platform vision