Fastrak AI Tech Stack

AI-powered product development platform with on-device ML and real-time sync

Technology, Information and Internet Newark, California 11–50 employees Founded 2024 Privately Held

Fastrak AI pairs on-device machine learning (Core ML, TensorFlow Lite, ExecuTorch) with cloud backends (PostgreSQL, Redis, vector databases) to ship AI-native applications at speed. The tech stack reveals a focus on low-latency inference and offline-first sync—they're actively adopting RAG and wrestling with real-time performance at scale. Engineering-led org (9 of 10 visible roles) with equal parts mid and senior hires, suggesting both hands-on execution and architectural guidance.

Tech Stack 49 technologies

Core StackTypeScript Figma Python Swift Cursor Pinecone Weaviate GraphQL PostgreSQL Redis AWS Cloudflare iOS Objective-C Core ML TensorFlow Lite ExecuTorch WebRTC Agora SQLite Core Data FFmpeg Cloudflare R2 CarPlay Claude Milvus pgvector Chroma REST GCP+17 more

AdoptingRAG

What Fastrak AI Is Building

◆Challenges

Low-latency inference
Real-time sync
Scalable vector database
Scaling to high volume usage spikes
Optimizing latency and connectivity
Ensuring security-first cloud architecture
Developing ai image and video generation workflows
Optimizing ai pipelines for quality and efficiency

▲Active Projects

On-device ml features including wake word detection and voice activity detection
Real-time video calling with ai-generated memory overlays
Offline-first architecture with reliable cloud sync
Frontend for ai video/audio creation, editing, and automation workflows
Ai-powered video/audio systems
Internal developer tooling for automation and content workflows
Vector database systems for family memory storage
Rag pipelines for contextual ai responses
Real-time sync systems for messaging and media
Esp32-based system development

Hiring Activity

Minimal10 roles · 0 in 30d

Department

Engineering

Security

Seniority

Mid

Senior

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About Fastrak AI

Fastrak AI is a software development studio combining AI automation with human oversight to accelerate product delivery. Founded in 2024, the company works with enterprise teams to move from concept to production without expanding headcount. The platform spans on-device ML features (wake word detection, voice activity detection), real-time video and audio systems with AI-generated overlays, and RAG-powered contextual responses. Infrastructure runs on PostgreSQL, Redis, and vector databases (Pinecone, Weaviate, Milvus) with Cloudflare R2 for media storage, enabling offline-first architectures with reliable sync.

HeadquartersNewark, California

Company Size11–50 employees

Founded2024

Hiring MarketsSyria

Frequently Asked Questions

What tech stack does Fastrak AI use?

TypeScript, Python, Figma, iOS/Swift, TensorFlow Lite, Core ML, ExecuTorch, PostgreSQL, Redis, Pinecone, Weaviate, Milvus, Claude, Cursor, AWS, GCP, and Cloudflare. They're actively adopting RAG patterns.

What is Fastrak AI working on?

On-device ML features (wake word, voice activity detection), real-time video calling with AI memory overlays, offline-first sync systems, vector databases for family memory storage, RAG pipelines, and internal automation tooling.