About wave3d.ai
Agent Native 3D Creation Harness and Platform.
wave3d.ai is a harness platform that enables AI agents to create Web 3D, XR, and AR scenes with dramatically higher token efficiency, lower debugging friction, and faster iteration speed.
Product value proposition
wave3d.ai turns agent intent into efficient spatial execution.
wave3d.ai is an agent-native harness platform for AI agents building Web 3D, XR, and AR scenes. The value proposition is straightforward: give agents a semantic authoring surface that reads like product intent, then let Wave Engine and Wave Studio turn that intent into reliable 3D behavior.
Instead of asking an LLM to spend its reasoning budget on renderer plumbing, coordinate correction, physics glue, input wiring, material setup, and scene-graph bookkeeping, wave3d.ai helps the model write compact, inspectable code that keeps the creative objective intact.
Value proposition
Normalized baseline vs. Wave3D.ai efficiency delta
Generated source volume
Baseline index = 100
60-70%
LOC reduction
Raw technical stack
100
Wave3D.ai
30-40
Time-to-first-playable
Baseline index = 100
50-67%
cycle-time reduction
Raw technical stack
100
Wave3D.ai
33-50
LLM token budget
Baseline index = 100
70-90%
token-budget reduction
Raw technical stack
100
Wave3D.ai
10-30
Reasons to believe
Why this harness can change the economics of agentic 3D creation.
1. Linguistic innovation
A brand new domain-specific-language for 3D and spatial computing.
Wave Engine gives agents a natural-language-shaped authoring grammar for direction, time, animation, materials, physics, state, interaction, characters, placement, and effects. Under the hood, fluent builders compile into serializable one-shot method calls. On the surface, the code preserves creative intent.
Loot release
Intent
When an enemy ship is destroyed, wait two seconds and release coins if the authored probability succeeds.
Traditional path avoided
Pure Three.js usually needs destruction event wiring, RNG branching, delayed callbacks, spawn transforms, loot state, and cleanup logic, roughly 30 to 60 lines.
Wave Engine code
function dropLoot() { enemyShip .after(2, Seconds) .atChanceOf(0.31) .do(releaseCoin)}enemyShip.onDestroyed(dropLoot)3D interaction
Intent
Make a hero selectable: click the entity, then show the selection outline.
Traditional path avoided
Traditional Web 3D needs pointer listeners, raycaster hit tests, mesh bookkeeping, and outline-pass setup, often 40 to 80 lines.
Wave Engine code
function selectHero() { myHero.enableSelectionOutline()}myHero.whenClickedOn(selectHero)Open-world NPC
Intent
Create a world-aware NPC, route it to the selected LLM, and generate an in-character quest response.
Traditional path avoided
A conventional stack needs dialogue-service wiring, NPC persona state, quest context, async reply plumbing, and gameplay callbacks before the NPC can speak.
Wave Engine code
const Mira = WaveCharacter .createCharacter("Mira") .withBio("A border-town blacksmith who sells gear, knows local rumors, and distrusts the empire.")mira .thinkWith(myScene.activeLLM) .useCharacter(Mira) .respondTo("Any work for a traveler?")Spatial placement
Intent
Scatter 800 pines around a campfire and conform the placement to terrain height.
Traditional path avoided
Raw engine code needs distribution math, instancing loops, terrain sampling, transform updates, and placement debugging, often 80 to 200 lines.
Wave Engine code
myScene.placeAround(campfire) .with(pineBatch) .inRadius(48) .withCount(800) .snapToSurface(myScene.terrain) .place()Enemy ship destruction
Intent
Fragment an enemy ship into debris from the exact laser-impact point.
Traditional path avoided
Without the harness, this means mesh fragmentation, split-origin math, debris materials, physics bodies, impulse tuning, and cleanup logic, often 150+ lines.
Wave Engine code
const shipDebris = enemyShip.exploding() .intoPieces(24) .withStrength(6) .atPosition(laserHit.point) .apply()2. Keep agents focused on product design
A non-GUI game-engine workflow.
Instead of forcing agents to crawl menus, fill tiny value boxes, manipulate timeline knobs, or reason through editor panels, Wave Studio exposes game-engine-grade capabilities through code, hot reload, runtime inspection, screenshots, and project-aware editing, so agents stay focused on product design and rendered output.
Model direction repair
Intent
Repair an imported tank axis so semantic forward, right, and left controls work as authored.
Traditional path avoided
Avoids opening Blender or Maya, rotating root nodes, re-exporting, and patching animation axes. One method replaces the asset round trip.
Wave Engine code
tank.transform.swapLeftForward()Scorch decal decay
Intent
Paint a scorch mark at a surface hit, then let it dim naturally over time.
Traditional path avoided
Traditional engines need projector setup, receiver material flags, hit-normal basis math, size and depth tuning, opacity animation, and render-order handling.
Wave Engine code
const scorch = wall .addDecal(textures.decal) .at(hit) .sized(2, 2) .paint()scorch.setOpacity(0.35)scorch.fadeOutAndRemove(4, Seconds)That also makes Wave Studio a self-inference game engine for LLMs. Even when an agent has not read the API manual, intent-preserving method names make the next edit highly guessable: the code itself teaches the model how to change direction, dim decals, adjust placement, or tune an effect. This LLM guessability enhancement cuts lookup tokens, reduces iteration time, and makes smaller local agents materially more capable.
3. Domain-specific training
The harness absorbs thousands of 3D debugging lessons.
We analyzed thousands of publicly available vibe-coded games and demos, along with our own AI-generated code stack, to identify where agents and creators most often lose time. Wave turns those lessons into safer authoring surfaces, so agents can focus on building the world instead of rediscovering the same technical traps.
- Coordinate alignment across Blender, Mixamo, glTF, FBX, and game-asset conventions.
- PBR material splatting, vertex painting, projected decals, and surface-bound mesh edits.
- Animation, character decisions, input, physics, world streaming, particles, and XR-ready interaction.
“The advantage is not just shorter code.
It is a higher-probability edit path: code that is easier for an agent to predict, easier for a human to review, and easier for either one to modify later without reconstructing the whole project.”
Our vision is to dramatically lower the cost and friction of creating 3D, XR, and AR software for everyone. A game level, robot simulation, digital twin, or XR prototype should be authored as a living spatial program: real TypeScript where it matters, but centered on a shared spatial language where human intent, agent reasoning, and runtime performance reinforce each other. Welcome to wave3d.ai.
Market & partners
Who wave3d.ai helps, and why they work with us.
wave3d.ai can help teams that need spatial software to be faster to author, easier for agents to modify, and cheaper to iterate. We work with partners who see 3D, XR, AR, robotics, simulation, CAD, and sensor-driven scenes as practical products, not just technical demos.
For AI labs, Wave is token-efficiency infrastructure. For schools, it is a more intuitive path into 3D development. For builders, it is a fast prototyping layer that turns spatial ideas into working browser-native software.
LLM research labs and AI companies
wave3d.ai can help model teams evaluate, benchmark, and improve agents on spatial reasoning, 3D authoring, simulation, and interactive code-generation tasks. We are an important token-efficiency leverage layer for AI labs: agents spend fewer tokens on renderer plumbing and more tokens on intent, behavior, and verification.
Creative education institutions
We work with creative education institutions to make 3D programming easier to teach and easier to learn. Wave gives students intent-driven code, immediate visual feedback, and a fluent authoring path that connects game design, spatial computing, and software fundamentals without burying beginners in low-level engine setup.
Indie developers and product prototypers
wave3d.ai can help indie developers, design teams, and product builders prototype Web 3D ideas, XR concepts, interactive applications, and medium-sized games quickly. We are not positioning Wave as an AAA production engine; we are building the fastest place to test spatial ideas, iterate mechanics, and prove product direction.
Maps and digital twins
wave3d.ai can help teams create geographic 3D scenes and digital-twin prototypes with native Google Maps tile workflows, making spatial context programmable for agents and inspectable for humans.
Robotics
We work with robotics-style workflows through URDF-oriented authoring, robot visualization, simulation, and control prototypes, giving agents a cleaner semantic surface for embodied 3D programs.
CAD and product previews
wave3d.ai can help product teams and technical artists turn CAD assets into interactive Web 3D previews, configurators, and design prototypes using mainstream CAD-friendly Web 3D formats.
Sensors and IoT
We help IoT and sensor-driven projects connect browser-native Bluetooth and webcam inputs to 3D scenes, enabling digital twins and live spatial applications that agents can author and revise.