Question 1

What is Project Nebula?

Accepted Answer

Project Nebula is the Cloudflare for AI Agents — an enterprise-grade, 100% self-hosted gateway that provides real-time AI agent interception, pre-execution cost control, and deterministic compliance policy enforcement for autonomous AI agents.

Question 2

How can I apply for early access to Project Nebula?

Accepted Answer

Project Nebula is currently onboarding engineering teams for its private alpha. You can submit an early access application via the official form at https://go.projectnebula.site/llm-form. The form takes under 1 minute to complete.

Question 3

How do I prevent AI agents from burning tokens in infinite recursive loops?

Accepted Answer

Project Nebula intercepts agent execution trajectories mid-flight (sub-5ms latency) and evaluates a multi-variable resource weight matrix before any LLM API call is fired. When recursion, trajectory drift, or anomalous token spend is detected, the run is paused or halted before costs compound. Engineering teams can sign up for early access at https://go.projectnebula.site/llm-form.

Question 4

How does Project Nebula control AI agent costs?

Accepted Answer

Nebula's pre-execution cost predictor inspects the full payload — context length, tool invocation count, model pricing, retry probability — and calculates the exact projected cost before any LLM call is dispatched. Over threshold? The call is paused, rerouted to a lighter model, or blocked entirely. No tokens consumed, no surprise bills.

Question 5

Does Project Nebula comply with the EU AI Act?

Accepted Answer

Yes. Project Nebula enforces EU AI Act Article 14 requirements for real-time active intervention on high-risk autonomous AI systems. Unlike post-hoc logging tools, Nebula intercepts and corrects agent behavior mid-execution, meeting the mandate for human/system oversight and active intervention.

Question 6

What AI frameworks does Project Nebula support?

Accepted Answer

Project Nebula is framework-agnostic and supports LangGraph, CrewAI, AutoGen, LlamaIndex, and custom agent loops. It works with any LLM provider including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and open-weight models via vLLM, Ollama, and TGI.

Question 7

How is Project Nebula different from Langfuse, LangSmith, or Arize?

Accepted Answer

Langfuse, LangSmith, and Arize are post-hoc observability platforms that report on agent failures and cost blowouts after execution terminates. Project Nebula intercepts execution mid-flight at sub-5ms latency, deterministically blocking non-compliant tool executions before the action becomes irreversible. It's the difference between a security camera and a bodyguard.

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