TensorOpera AI

Name: TensorOpera AI
Brand: TensorOpera AI

AI Native

Turn Your Idea into Business-Ready AI Agents Faster build with prompts, orchestrate in chats, grow on scalable infra

Est 2022|Valuation $58M|Raised $13.5M|10 Ref Customers

LinkedIn 3K|Website|FTEs 25|HQ Palo Alto, California, US

	TensorOpera AI	Runpod	Modal
Starting Price (platform)	Starter free tier; Advanced priced in the low-hundreds/month (+ compute); Enterprise: contact sales	Usage-based (no single base fee highlighted publicly)	Starter free tier + compute; Team tier in the low hundreds/month + compute
Compute pricing example (H100 class)	H100-class pricing examples are listed on the vendor pricing page (example figures shown publicly)	Serverless H100 pricing shown on pricing page (varies by worker type)	H100-class pricing available and metered per second in vendor materials
Typical Use Case	Teams seeking a combined agent, serving, training, and federated learning platform (vendor positioning)	Teams seeking a large GPU marketplace and serverless endpoints	Serverless Python-native infrastructure for batch/inference/training with developer ergonomics
Key Strength	Broad functional scope and a decentralized GPU scheduling narrative (vendor claim)	Large GPU catalog and visible pricing; developer-focused infrastructure	Strong serverless ergonomics and metered billing; explicit enterprise options noted
Key Weakness	Limited mainstream third-party review coverage; compliance documentation not clearly public	Not a dedicated agent platform; agent tooling is typically built separately	Not positioned as a federated learning platform; agents typically require custom tooling

	TensorOpera AI	Runpod	Modal
Starting Price (platform)	Starter free tier; Advanced priced in the low-hundreds/month (+ compute); Enterprise: contact sales	Usage-based (no single base fee highlighted publicly)	Starter free tier + compute; Team tier in the low hundreds/month + compute
Compute pricing example (H100 class)	H100-class pricing examples are listed on the vendor pricing page (example figures shown publicly)	Serverless H100 pricing shown on pricing page (varies by worker type)	H100-class pricing available and metered per second in vendor materials
Typical Use Case	Teams seeking a combined agent, serving, training, and federated learning platform (vendor positioning)	Teams seeking a large GPU marketplace and serverless endpoints	Serverless Python-native infrastructure for batch/inference/training with developer ergonomics
Key Strength	Broad functional scope and a decentralized GPU scheduling narrative (vendor claim)	Large GPU catalog and visible pricing; developer-focused infrastructure	Strong serverless ergonomics and metered billing; explicit enterprise options noted
Key Weakness	Limited mainstream third-party review coverage; compliance documentation not clearly public	Not a dedicated agent platform; agent tooling is typically built separately	Not positioned as a federated learning platform; agents typically require custom tooling

01Competitive Landscape