Decentralized, Sub-second
Inference Gateway
for Autonomous AI Agents
Production-grade distributed inference serving with OpenAI-compatible APIs. Route agent requests across GPU worker nodes with sub-second latency and streaming responses.
Product
What AgentFlow Engine does
AgentFlow Engine is a distributed LLM inference gateway. Agents and applications send OpenAI-compatible requests; we schedule them onto GPU workers running vLLM and stream tokens back with low latency.
OpenAI-compatible API
Drop-in /v1/chat/completions for agent frameworks. Streaming SSE responses with standard auth headers.
GPU worker orchestration
Route inference across NVIDIA L4 / A10G workers with vLLM, continuous batching, and health-aware failover.
Latency-first routing
Target sub-second TTFT for agent loops. Benchmarks published as Q4 2026 beta targets under controlled load.
Cloud-native deploy
Dockerized gateway + workers for Azure, GCP, and AWS GPU instances. Built for 24/7 agent traffic.
Built for AI agents
Designed for autonomous agent workloads — high request rates, short contexts, and reliable streaming.
Who it is for
Teams shipping agent products that need private or multi-GPU LLM inference without rewriting their OpenAI client.
Beta Target Benchmarks
Projected inference performance for Q4 2026 GPU beta (vLLM load tests)
| Model | GPU | TTFT (P50) | TPS | Status |
|---|---|---|---|---|
| LLaMA-3-8B-Instruct | NVIDIA L4 | ~142ms | ~847 | beta target |
| LLaMA-3-70B-Instruct | NVIDIA A10G | ~318ms | ~124 | beta target |
| Mistral-7B-Instruct-v0.3 | NVIDIA L4 | ~98ms | ~1,024 | beta target |
| Mixtral-8x7B-Instruct | NVIDIA A10G | ~276ms | ~186 | beta target |
Estimated targets · vLLM 0.6.x · batch size 1 · 512 token context · validated in 90-day cloud GPU beta
Architecture
Distributed node orchestration with intelligent request routing
Smart Router
Latency-aware load balancing across GPU nodes
Streaming
Server-sent events for real-time token delivery
vLLM Backend
PagedAttention with continuous batching
API Integration
OpenAI-compatible endpoints — drop-in replacement for agent frameworks
curl https://api.agentflowengine.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AGENTFLOW_API_KEY" \
-d '{
"model": "llama-3-8b-instruct",
"messages": [
{"role": "user", "content": "Summarize the latest agent task."}
],
"stream": true,
"max_tokens": 512
}'Company
About the company
AgentFlow Engine is developed by Jinsol Company, a Korean software business operated by founder Jinsol Lee. We build cloud-native inference infrastructure so AI agent products can run production LLM workloads on GPU clusters with a familiar OpenAI-compatible API.
- Legal entity
- 진솔컴퍼니 (Jinsol Company)
- Business registration
- 582-70-00693
- Product brand
- AgentFlow Engine
- Founder
- Jinsol Lee (이진솔)
- Industry
- Software development & AI infrastructure
- Stage
- Bootstrapped · Early stage · Founded 2025
- Location
- Republic of Korea
- Website
- https://www.agentflowengine.com
What we are building
A production inference gateway for autonomous agents: request routing, GPU worker health checks, streaming completions, and deployment scripts for major cloud GPU instances. Public beta targets are published on this site; live health is available at our API subdomain.
Founder
Jinsol Lee — Information Security Engineering background (Sangmyung University) and freelance software development. Currently shipping AgentFlow Engine and preparing a 90-day cloud GPU beta.