AI has reshaped knowledge work. It hasn't shown up for field technicians yet. They juggle many tools to document one repair: voice notes in one app, photos in another, part requests typed on a phone between jobs. Helpi replaces the whole stack with a voice-first mobile app and a synced web CRM. The technician talks, AI listens. It structures the notes, reads what the job needs, and drafts the part request straight to the supplier.

Parts suppliers run their whole business through email. Helpi turns every incoming message into a task the team can route, own, and close. An AI works alongside at every step. It looks up part prices. It pulls product details from the catalog. It drafts the reply. It hands the task off to the right person automatically. Same inbox the team already uses, now with a brain.

Most fitness apps drop you with cold interfaces; personal trainers fix this at $50–150/hour. GymVox closes the gap with a voice-first AI Trainer (name user-configurable) and a stack of AI superpowers in your pocket: realtime voice coaching, fitness Q&A, exercise-form analysis, body-photo progress checks, gym-equipment recognition, diet planning, nutrition & workout journals, and an adaptive workout generator backed by a 920-exercise atlas that scales beginner → advanced. 80% of a trainer's value at 5% of the cost.

Not a plugin — a platform. Each tenant gets an isolated Product with its own marketplace of AI services (chat, knowledge search, recommendations, analytics) and a composable widget stack mounted on their store. Thin Shopify / Woo bridges embed the widget; the same engine powers GAIO — the AI assistant we built for iMain (MLM) — and extends to any commerce surface next.

A parent photographs any page from a textbook; an AI pipeline reads it, extracts the key concepts, and injects them as live questions inside real arcade mini-games — Flappy with Pix the robot, Whack-a-Mole, more on the way. The child plays, learns, and asks for more.

An EV owner requests a charge — a verified driver picks up the car, takes it to the fastest nearby station, and brings it back. Owner never leaves the chair. Each trip also feeds a live charger-intelligence layer: real wait times, queue length and price per station, updated by the driver network itself.

Most content tools help you edit — AVM helps you ideate at scale with an AI critic built in. Pick a niche + chaos level, and the pipeline generates concepts, filters by virality DNA (conflict, irony, shareability), pivots weak ones, scores emotional arousal, and runs 5-persona audience simulations. Only ~2% of concepts survive — those are the ones worth making.

Existing tools watch passively, spam without context, or generate copy in a vacuum. Agents Studio reads full discourse, distills insights into a persistent knowledge base (pgvector + Postgres), and proposes comments grounded in what the community actually rewards. A self-improving Learning Engine modifies its own strategy — every decision must move the agent closer to the campaign goal.

Every project on this deck started here. You drop in a one-liner. It interviews the founder, maps competitors, pulls keywords, challenges the weak assumptions, and spits out a brief tight enough for engineering to start that same day. The "nine-day MVP" cadence runs on this.

Two engines working as one. Layout-Generator spins up a library of 90+ visually distinct designs from a single brief, each enforced by a HARD STYLE DNA system so every output is unique. LP-Generator then takes the chosen design and the startup’s materials and ships a working Next.js app via two commands: /lp-research builds the strategy and copy, /lp-create turns the design HTML into deployed React components. The whole pipeline is how Nexly Lab produces its own landing pages.