Mobiusi

Moye

The Multimodal Data Foundry for AI

Enabling scalable data production, standardized packaging, and quality verificationfor multimodal inputs — turning raw collection into trainable, deliverable,and traceable asset-grade datasets.So data enters the AI lifecycle as production-ready, reusable training assets.

Why Moye Exists

Moye exists because the AI world lacksscalable data production, verifiable quality standards, and deliverable data assets.

  • Data is abundant, but cannot enter training pipelines

    • Raw data is often noisy, incomplete, inconsistent, and semantically unclear,making it difficult to use directly for training, alignment, or evaluation.

    [ Data exists, but is not AI-ready. ]

  • Multimodal production lacks a unified operating system

    • Each modality requires different workflows. Toolchains are fragmented,pipelines are hard to reuse, and delivery quality is difficult to stabilize—preventing data production from scaling like compute.

    [ AI's bottleneck is not data volume - it's data oduction. ]

  • Quality is hard to verify, compliance is hard to operationalize

    • Without standardized QA frameworks and verifiable deliverables,providers cannot prove quality, consumers cannot reuse with confidence,and compliance boundaries remain difficult to manage at scale.

    [ Data cannot become production-ready training assets. ]

Core Capabilities of Moye

Multimodal Pipelines

Unified, reusable pipelines for scalable multimodal production.

Cleaning & Standardization

Convert raw inputs into AI-ready standardized datasets.

Labeling & Alignment Support

Support alignment needs under a unified framework.

Quality Verification Loop

Measurable QA for consistent delivery.

End-to-End Traceability

Auditable logs across the full lifecycle.

Deliverable Asset Packaging

Ship acceptance-ready assets into Cubo and Rivo.

Schematic Blueprint

Continuous Data Stream
Raw Video_01
Voice Log_9
Contract.pdf
Script.py
Dataset.png
Graph.json

MOYE

Core Foundry

Processing Engine

Asset A1
Asset B2
Model X
Clean DB

Data Types Processed by Moye

Multimodal Raw Data

Raw text, images, video, audio, and sensor streams refined into structured, AI-ready datasets.

[ Cleaning ]·[ Normalization ]·[ Multimodal packaging ]

Training-Ready Datasets

Datasets prepared for pretraining and fine-tuning with consistent formats and stable quality.

[ Pretraining ]·[ Fine-tuning ]·[ Evaluation ]

Temporal & Event Sequence Data

Logs, events, and sequential signals processed into consistent timelines for state and behavior learning.

[ Time-series ]·[ Event chains ]·[ State evolution ]

Industry-Specific Datasets

Domain datasets refined for healthcare, industrial systems, finance, retail, robotics, and private deployments.

[ Vertical models ]·[ Domain agents ]·[ Private deployment ]

Structured & Graph-Ready Data

Structured, relational, and entity-linked datasets prepared for graph integration and reasoning workflows.

[ Entities ]·[ Graph integration ]·[ Reasoning-ready ]

Derived, Augmented & Synthetic Data

Augmented and derived datasets generated under controlled rules to expand coverage for rare or long-tail scenarios.

[ Augmentation ]·[ Rare scenarios ]·[ Coverage expansion ]