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When Regulus is the right call. When it isn't.

Four honest comparisons against the alternatives most regulated teams consider. Each page lists when to pick Regulus, when to pick the alternative, and the decision criteria in between.

  • vs Guardrails libraries

    Regulus vs NeMo Guardrails / Guardrails AI / generic guardrails libraries

    Guardrails libraries operate on the prompt/response boundary. Regulus operates on the full agent trajectory — purpose limitation, residency, dual-control, audit envelopes.

  • vs LangChain alone

    Regulus vs LangChain alone

    LangChain is an agent-building toolkit. Regulus is a compliance plane targeting Google ADK as primary runtime. An alt-runtime module wraps LangChain4j; new work lands on ADK first.

  • vs Vertex AI alone

    Regulus vs Vertex AI alone (no compliance plane)

    Vertex AI is the runtime. Org Policy + VPC-SC + Assured Workloads handle the data plane. The agent's decision plane — purpose limitation, audit, kill switch — is the layer Regulus fills.

  • vs Building in-house

    Regulus vs building the compliance plane in-house

    Every regulated team has built at least the audit-log and kill-switch pieces themselves. Here's where the gaps usually show up after 6–12 months, and where Regulus differs.

Regulus

Where Google ADK ends, regulated builds begin.

A project by Neul Labs. MIT-licensed. Java 21.

Product

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  • How it works
  • Regulations
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For

  • For platform engineers
  • For AI governance leads
  • For MRM / SS1/23
  • For solution architects

Concepts

  • Plugins
  • Services
  • Regulations
  • Frameworks
  • Coverage matrix
  • Security model

Compare

  • vs Building in-house
  • vs Guardrails libraries
  • vs LangChain alone
  • vs Vertex AI alone

Resources

  • Install
  • FAQ
  • About
  • Contact
  • Technical docs ↗
  • GitHub ↗

© 2026 Neul Labs. Regulus is open source under the MIT license.

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