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Alternatives

Products that do what LLMSafe — Zero-Trust AI Security Gateway does

A zero-trust security layer between your apps and LLMs

  1. 1

    Use any AI model with just one API

    2025

  2. 2

    Your AI privacy protection

    2024

  3. 3

    Connect, observe & control LLMs, MCPs, Guardrails & Prompts

    Dec 2025

  4. 4

    Security gateway for LLM agents

    Feb 2026 · cencurity.com

  5. 5
    ZenMux382

    An enterprise-grade LLM gateway with automatic compensation

    Feb 2026 · zenmux.ai

  6. 6

    The best LLM on every prompt

    2024

  7. 7
    LLMWare358

    Dev tool to make AI apps to deploy privately or locally

    2024

  8. 8

    Zero-trust security gateway for AI agents

    Jun 2026 · solongate.com

  9. 9
    AskCodi230

    Custom LLMs, without training. Use via openai compatible api

    Nov 2025

  10. 10TL
  11. 11
    Edgee196

    The AI Gateway that TL;DR tokens

    Feb 2026 · edgee.ai

  12. 12

    A zero-trust API Gateway for your AI Agents.

    Jun 2026 · zerotrust-agents.com

  13. 13

    Guardrails and Provenance for enterprise AI control

    Mar 2026 · console.agumbe.ai

  14. 14

    Global AI safety platform for red-teaming and trust

    Dec 2025

  15. 15

    Self-hosted PII firewall for LLMs — policies, audit trail

    Jun 2026 · github.com

  16. 16OS

    Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…

    Oct 2025 · archestra.ai

  17. 17

    The firewall for AI prompts. Drop-in security for LLM apps.

    Dec 2025

  18. 18MG

    Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…

    Dec 2025 · truefoundry.com

  19. 19

    The Confidential AI Gateway

    Dec 2025

  20. 20

    Noisegate: a differential privacy gateway that lets an untrusted LLM agent query sensitive data over MCP (Model Context Protocol), with a formal guarantee no individual's record can leak even if the agent is adversarial - enforcement lives in trusted code below the model, validated by a runnable att

    Jul 2026 · github.com

  21. 21CL

    We're excited to launch compliant-llm: an open-source toolkit that helps infosec and compliance teams audit AI agents against regulatory frameworks like NIST AI RMF, ISO 42001, and OWASP Top 10. Infosec and compliance teams are now responsible for tracking security and compliance risks of a growing number of AI agents across external and internal apps and third-party vendors. compliant-llm gives you a way to: - Define and run comprehensive red-teaming tests for AI agents - Maps test outcomes to compliance frameworks like NIST AI RMF - Generate detailed audit logs and documentation -…

    2025 · github.com

  22. 22

    Automated SOC2/HIPAA ledgers & LLM governance in one click.

    Mar 2026 · aitrustos.app

  23. 23LS

    LLMStack is a low-code platform that can be used to build LLM apps, chatbots and integrate AI experiences into existing products/workflows. It comes with everything out of the box that one needs to build LLM apps locally. It can also be used in a multi-tenant setting, making it available for everyone to use in an enterprise. Some highlights of the platform: - Chain multiple LLM models allowing for complex pipelines - Includes a vector database and necessary connectors to help enrich LLM responses with private data - App templates tailored to specific use cases to quickly build LLM apps…

    2023 · github.com

  24. 24PT

    Hi HN, We’re @sumants and @rmehtany, working on Pontus. Pontus makes it easy to use AI with privacy embedded. We were concerned about the volume of personal data that goes to large LLM models without protection. We tried find an easy solution where didn’t change the simple apis given by LLM providers. However, most required you to invest significant engineering effort. We wanted privacy and LLMs to be easy, so we built Pontus. Through a declarative YAML, we orchestrate a microservice with the most common element of the LLM stack. - Anonymize Prompts before it hits LLMs, yet keeps context on…

    2023 · github.com

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