Cost optimization
What an AI Agent Costs Per Conversation on AgentCore
- Pratik Kulkarni
- AI FinOps , AWS
- 28 Aug, 2026
You can read AgentCore's per-service rates straight off the AWS pricing page. What that page can't tell you — and what you actually need before you build a business on agents — is what one of your u
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When Is Self-Hosting an LLM Cheaper Than Bedrock?
- Pratik Kulkarni
- AI FinOps , AWS
- 26 Aug, 2026
Two questions send teams down this path: "our Bedrock bill is growing, should we run this on our own GPU?" and "we fine-tuned a Llama, where does it go?" For most teams the answer to both is no, a
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Cheaper Alternatives to AWS in 2026: What Each One Cuts
- Pratik Kulkarni
- Cloud Architecture , Cost Optimisation
- 21 Aug, 2026
There is no single cheapest alternative to AWS, because AWS bills are not shaped the same way. A bill dominated by EC2 has a different answer from one dominated by egress, RDS or GPU-hours. And severa
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Hetzner vs AWS: The Real Cost Difference in 2026
- Pratik Kulkarni
- Cloud Architecture , Cost Optimisation
- 21 Aug, 2026
For a standing 8-vCPU, 16 GB server, AWS charges about $212 per month on demand and Hetzner charges €20.99, or roughly $25. That is a factor of nine, and it is not a rounding error. The gap is also no
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What Is AI FinOps?
- Pratik Kulkarni
- AI FinOps , AWS
- 09 Jun, 2026
AI FinOps is the practice of making AI workload costs visible, attributable, and optimizable — applied to the specific economics of model inference, where the unit of cost is the token, not the instan
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AWS Bedrock Cost Structure: What You're Actually Paying For
- Pratik Kulkarni
- FinOps , AWS
- 05 May, 2026
AWS Bedrock looks simple from the outside — call an API, get a response, pay per token. The reality is that a production Bedrock setup has several distinct cost layers, and they behave very differentl
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Why Your AWS Bedrock Bill Makes No Sense (And How to Fix It)
- Pratik Kulkarni
- FinOps , AWS
- 30 Mar, 2026
When a startup says "our AWS bill is too high," the conversation almost always starts at the aggregate level — total monthly spend, a few large services, maybe a spike someone noticed. That's not wher
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