AI Development Infrastructure

Building the foundational tools and platforms that accelerate AI innovation and development

Data Infrastructure

Imagate Synthetic Data Engine

Imagate Synthetic Data Engine

Spec Legacy built Imagate, a Data-as-a-Service platform that removes one of AI’s biggest challenges—the shortage of high-quality, labeled datasets. Designed for enterprise R&D and AI teams, it generates unlimited, photorealistic training data with perfect annotations. The system uses 3D simulation engines like Unreal Engine, Houdini, and Blender to create detailed, procedural scenes on demand. Its scalable AWS EKS architecture supports large workloads, while an LLM-based interface lets users generate complex datasets from simple text prompts. Imagate reduces data preparation time from months to hours and lowers labeling costs by over 90%, accelerating AI development.

Voice Synthesis

Emotive Text-to-Speech Engine

Spec Legacy built an advanced Text-to-Speech engine that generates voices in over 25 emotional tones for gaming, media, and interactive entertainment. It delivers expressive, human-like speech through a training process that blends professional voice recordings with refined audio source separation. A custom dataset was created using 25 voice actors performing emotion-specific scripts, enhanced with clean vocal tracks extracted from movie audio using Demucs. Developed with the Coqui TTS framework on Python and PyTorch, the system shows Spec Legacy’s expertise in building emotion-aware TTS models that make digital experiences more natural and engaging.

Emotive Text-to-Speech
MLOps

AI Model Training Pipelines

AI Model Training Pipelines

Spec Legacy develops full-scale AI training infrastructure that manages every stage of the machine learning process from data handling to deployment. The system includes automated data versioning, distributed GPU training, hyperparameter tuning, and continuous performance evaluation. It supports both supervised and unsupervised learning, with tailored workflows for vision, language, and reinforcement models. Using MLflow and Weights & Biases, all experiments are tracked for easy comparison and reproducibility. The platform dynamically scales resources based on dataset size and model needs, offering real-time metric monitoring and early stopping to boost efficiency and shorten development cycles.

Deployment

Model Serving & Deployment Platform

Spec Legacy’s model serving and deployment platform delivers secure, scalable infrastructure for running AI models in production. Built on Kubernetes with Istio, it supports canary releases, A/B testing, and controlled rollouts with automatic rollback for safety. The system manages multiple model versions at once, enabling smooth updates across varied use cases. Real-time dashboards track latency, throughput, and performance to ensure reliability and speed. With built-in feature stores maintaining online and offline consistency, the platform handles millions of requests efficiently, keeping inference times below 100ms for real-time applications across industries.

Model Serving Platform

AI Infrastructure Technology Stack

Comprehensive tools and platforms powering our AI development and deployment ecosystem

AWS EKS
Kubernetes
Unreal Engine
Houdini
Blender
Python
PyTorch
Coqui TTS
Audio Processing
MLflow
Weights & Biases
Istio
Docker
AWS S3
LLM Integration
GPU Clusters
GitOps
Feature Store
AWS EKS
Kubernetes
Unreal Engine
Houdini
Blender
Python
PyTorch
Coqui TTS