Parasail Blog
Product updates, engineering deep dives, and thought leadership from the Parasail team.
How Parasail built one AI agent for inference operations
The hard part wasn’t putting an AI agent in Slack. It was embedding trusted sources, reviewed calculations, and safe inference-operations workflows.
EngineeringBuilding sub-second LLM inference for global AI traffic
A fast model isn't a fast API. Here's how we worked backward from a 600ms p99 budget — Cloudflare Workers at the edge, WireGuard straight to the GPU — without giving up Kubernetes, global capacity, or fault tolerance.
EngineeringPrefill vs. decode in LLM inference
Understand how prefill and decode shape time to first token, streaming performance, KV-cache pressure, and LLM serving decisions.
GuidesParasail to combine NVIDIA AI infrastructure with d-Matrix accelerators to achieve 10x faster token generation
Parasail to deliver faster, more cost-efficient tokens by pairing NVIDIA Hopper and Blackwell GPUs with d-Matrix Corsair accelerators
ProductBeyond the frontier: How to build a defensible AI inference infrastructure
Closed model dependency is becoming structural liability. Here's the framework for building a reliable AI inference architecture.
ProductFaster autoscaling for vLLM: Restoring from snapshots instead of starting cold
Cold-start latency is one of the biggest bottlenecks when scaling inference. Parasail's model snapshotting saves and restores CPU and GPU process state to bring vLLM replicas online 3-5x faster than rebuilding from scratch.
Engineering