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Controlling Generative AI Costs in the Enterprise with Otoroshi LLM Extension

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Controlling Generative AI Costs in the Enterprise with Otoroshi LLM Extension

Generative artificial intelligence (generative AI) is revolutionizing the enterprise: smart assistants, automation, content generation… use cases are multiplying fast.

But this growing adoption comes with a major challenge: managing the usage costs of large language models (LLMs) such as ChatGPT, Claude or Mistral.

Many companies end up facing a bill that keeps climbing with no real control over it, because of usage that is intensive, poorly governed or scattered across teams.

That’s exactly the need we built Otoroshi LLM Extension for: a solution to take back control of AI costs in the enterprise, without sacrificing innovation.

Why monitor and optimize LLM usage in the enterprise?

Here’s what we see in the field:

  • Monthly LLM costs skyrocket as usage grows (especially with GPT-4).

  • A lack of visibility into who uses what, how, and at what price.

  • No quotas or usage rules for employees.

  • No distinction between simple tasks (which could use a free or local model) and complex ones.

💡 The result: a loss of budget control, a risk of overconsumption and unjustified spending.

Otoroshi LLM Extension: the solution to control AI costs

Otoroshi LLM Extension is a strategic layer that acts as a single entry point for all AI usage across your company.

It lets you monitor, secure and govern LLM usage, while significantly reducing costs.

Automatically reduce LLM calls with smart caching

Many requests are repetitive (same question, same context).

Rather than paying again every time, Otoroshi LLM Extension reuses previous responses.

  • Configurable prompt-based caching

  • Responses stored temporarily to avoid needless billed calls

  • Ideal for internal assistants or automated FAQs

🎯 Impact: up to 50% fewer billed requests

Smart routing to the right model at the right time

Not every use case needs GPT-4.

  • For simple tasks: open source models hosted in-house

  • For complex cases: fallback to high-performance models (GPT, Claude)

  • Ability to create custom rules based on the type of request or the user

🎯 Impact: optimized usage, a lighter bill

Access, quota and budget management per team or department

Control who has access to AI and how many requests are allowed, and keep track of budgets.

  • Set consumption caps (number of requests or cost)

  • Assign API keys per user or service

  • Enforce AI governance policies

🎯 Impact: no more runaway consumption, usage aligned with your strategy

Clear dashboards for better governance

You can only optimize what you measure.

  • LLM usage broken down by department, user or project

  • Real-time cost estimates (per token or per model)

  • Export and reporting for IT leadership and procurement teams

🎯 Impact: reliable budget management that supports decision-making

Automatic prompt rewriting to reduce token usage

Some prompts are needlessly long or poorly worded.

Otoroshi can simplify or optimize them automatically before they are sent.

  • Removal of redundancies

  • Semantic optimization to limit tokens

  • Identical results, lower cost

🎯 Impact: a direct reduction in billed token consumption

Built-in security and compliance

By centralizing all AI calls:

  • You block unauthorized usage

  • You prevent sensitive data leaks

  • You strengthen GDPR compliance and internal security

Innovation under control, budget in check

Adopting generative AI shouldn’t mean losing control of your budget.

With Otoroshi LLM Extension, you give your teams a secure, intelligent framework for using LLMs, while maximizing your return on investment.

🚀 Ready to take back control of your AI costs?

🔗 Explore the official documentation

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