Inference.ai

🖼️ Tool Name:
Inference.ai

🔖 Tool Category:
AI infrastructure / inference orchestration; it falls under DevOps, CI/CD & Monitoring (103) and Integrations & APIs (44) in your taxonomy.

✏️ What does this tool offer?
Inference.ai enables more efficient use of GPU resources by virtualizing them, allowing multiple AI models to run on the same hardware. 
It supports model training, fine-tuning, and inference (in production) such that you can run multiple workloads per GPU and improve utilization. 

⭐ What does the tool actually deliver based on user experience?
• Fractional GPU allocation — use parts of GPU capacity for light workloads. 
• Run multiple models on one GPU card concurrently. 
• Better throughput and cost efficiency — you “get more workloads with the same hardware.” 
• GPU virtualization layer and orchestration for inference infrastructure. 

🤖 Does it include automation?
Yes — it automates the scheduling, resource allocation, and orchestration of model inference tasks over GPU infrastructure so developers don’t have to manually partition or schedule. 

💰 Pricing Model:
Not fully public, likely enterprise / custom pricing depending on usage and GPU capacity.

🆓 Free Plan Details:
No clear mention of a free tier in the public information I found.

💳 Paid Plan Details:
The paid model would include higher usage, dedicated GPU pools, prioritized scheduling, and enterprise support.

🧭 Access Method:
• Through their web console / platform (you “Access the Console” on their site) 
• Integration via APIs / orchestration tools to connect inference jobs to the infrastructure.

🔗 Experience Link:

https://www.inference.ai