AI inference for growing businesses—from serverless APIs to custom inference solutions. 400+ models. 99.9% SLA. 24/7 technical support
San Mateo, California, US
Joined June 2025
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Infron retweeted
AI models evolve weekly. Your infra shouldn't have to.
With Alibaba Cloud, @InfronAI scales open-source models like Qwen with dedicated capacity across 5 global regions, provisioned in days with verifiable placement.
Read now: click.alibabacloud.com/m/200…
#Qwen #AI #LighthouseCustomerStories
Infron retweeted
Connect Infron to Codex with one prompt.
codex plugin marketplace add InfronAI/infron-codex-plugin
After installation, enable the infron plugin
Set INFRON_API_KEY in your shell
Tell me how to use Infron
That’s it. Codex can now learn how to use Infron’s unified AI APIs for:
- OpenAI-compatible chat completions
- Provider routing
- Search APIs
- Image, video, and audio generation
- Embeddings, reranking, and batch jobs
Build with one interface. Route across models and providers. Ship faster.
Infron retweeted
One magic prompt.
500+ frontier models instantly accessible.
With Infron’s llms-full.txt, your AI Agent can understand how to connect your app to the world’s leading LLM, Media, Search, and Agent models — through one unified gateway.
Just tell your Agent:
“Read and understand Infron from: infron.ai/llms-full.txt”
From there, it can learn the APIs, model usage, routing, fallback, gateway features, and integrations — and help your app plug into the global AI model ecosystem faster than ever.
Infron retweeted
Excited to share that our paper, “SEAR: Schema-Based Evaluation and Routing for LLM Gateways,” was accepted to @CAISconf 2026! 🎉
This work was done at @struktoai, in partnership with @InfronAI.
Paper: caisconf.org/program/2026/pa…
Infron retweeted
Still torn between Pay-as-you-go and reserved PT capacity? 🤔
It's one of the most common infrastructure dilemmas for AI teams today:
→ Pay-as-you-go gives you flexibility, but costs spiral unpredictably at scale.
→ Dedicated PT gives you cost control, but locks you in — even during off-peak hours.
Turns out, you don't have to choose.
@InfronAI has quietly solved this with a third path — a hybrid model that combines:
✔ Baseline capacity guarantees (no more peak throttling)
✔ Dynamic burst scaling (only pay for what you actually need)
✔ Agile model switching on weekly/monthly cycles
✔ Predictable costs without the long-term lock-in
If you're building production-grade AI applications or scaling SaaS workloads, this is worth a look.
Infron retweeted
做好一个AI聚合网关，太不容易了。
🖥️ 开发测试阶段 - 文本生成，视频生成，图像生成，每一个厂商的API接口格式都不一样，开发工期一拖再拖，错过了市场风口
👨🏻🏭 推广起量阶段 - 流量激增导致账号限流，和每一个原厂来来回回上百封邮件的沟通和在线会议，提交繁多的材料后，才仅仅提升了一点点账号的PT和Quota，看着满屏的429/500报错束手无策
⚡ 忘记做主从备份，泼天流量来的时候API突然挂了，只能无奈看着客户流失
💰 每月消耗数万美元的AI Tokens，却只能原价给原厂付费
现在有了 onerouter.pro 这些问题都迎刃而解，相信我们，我们是最懂初创企业痛点的AI聚合网关团队
现在加入 onerouter.pro 告别AI接入的痛苦，全身心投入到业务中
@OneRouter
