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Parasail Tech Stack

GPU compute network for distributed AI model deployment

Technology, Information and Internet San Mateo, California 11–50 employees Founded 2023 Privately Held

Parasail operates a global GPU compute marketplace connecting AI teams to on-demand inference and batch processing capacity without long-term contracts or cloud vendor lock-in. The stack is deep in optimization layers—vLLM, FlashAttention, SGLang, Triton, ROCm—indicating engineering effort concentrated on inference efficiency and cost reduction, which directly addresses the customer pain point of GPU deployment economics. Active projects span LLM support, real-time audio pipelines, and platform onboarding, suggesting a lean team (11–50 employees, founded 2023) moving quickly across both infrastructure and product-market fit.

Tech Stack 17 technologies

Core StackKubernetes PyTorch Python C++ JavaScript TypeScript Java Go vLLM SGLang FlashAttention CUDA ROCm XLA Jax Triton Spring Boot

What Parasail Is Building

◆Challenges

Cost and performance optimization of ai workloads
Vendor lock-in avoidance
Scalable ai infrastructure
Go-to-market motion
Pipeline from scratch
Optimizing gpu deployment cost
Scaling ai workloads
Security and data privacy
Cost inefficiencies and idle capacity
Vendor outages

▲Active Projects

Llm support platform
Vllm engine optimization
Flashattention integration
Pipeline from scratch
Playbook definition
Onboarding guidance
Ai-powered workflow prototypes
Llm-driven features
Real-time audio/voice pipelines
Ai platform deployment

Hiring Activity

Minimal6 roles · 0 in 30d

Department

Engineering

3

Ops

1

Sales

1

Seniority

Mid

2

Senior

2

Director

1

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About Parasail

Parasail provides on-demand GPU compute infrastructure for AI model deployment, targeting teams building with open-source models and evolving LLM stacks. The platform abstracts cloud complexity by intelligently routing workloads across a distributed GPU network, optimizing for latency, cost, and geographic preference. The company handles inference, batch processing, and real-time pipeline use cases. Engineering leadership is distributed across LLM support, vLLM optimization, and deployment automation; ops and sales roles reflect early-stage GTM motion and infrastructure reliability needs.

HeadquartersSan Mateo, California

Company Size11–50 employees

Founded2023

Hiring MarketsUnited States

Frequently Asked Questions

What is Parasail's tech stack?

Parasail's core stack centers on Kubernetes orchestration, vLLM and SGLang for LLM inference optimization, FlashAttention for attention kernels, CUDA and ROCm for GPU compute, and PyTorch/JAX for model execution. Frontend and backend use Python, C++, JavaScript, TypeScript, Java, Spring Boot, and Go.

What problems does Parasail solve?

Parasail addresses GPU cost optimization, vendor lock-in avoidance, scalable AI infrastructure, and idle capacity inefficiencies. The platform targets teams managing cost and performance trade-offs in LLM inference and batch workloads.

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