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AI Security Gateway VS @imqueue

Compare AI Security Gateway VS @imqueue and see what are their differences

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Contents:
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  3. ยป Reviews
  4. ยป Alternatives

AI Security Gateway logo AI Security Gateway

AI Security Gateway (AISG) is an AI firewall, LLM proxy & MCP Gateway that redacts 30+ PII types (text+vision), blocks prompt injections, smart-routes 600+ models, & enforces budgets โ€”2-line integration, loop detection, zero data retention.

@imqueue logo @imqueue

RPC over an inter-communication messaging queue for service-oriented Node & TypeScript back-ends. Self-describing services generate their own clients โ€” no boilerplate, no service discovery, no load balancer.
  • AI Security Gateway AI Security Gateway Landing Page
    AI Security Gateway Landing Page //
    2026-05-06
  • AI Security Gateway Dashboard
    Dashboard //
    2026-04-16
  • AI Security Gateway PII Protection Playground
    PII Protection Playground //
    2026-05-06

AI Security Gateway is the control layer between your application and any LLM provider. Change your base_url. Two lines of code. Your prompts are secured before they leave your infrastructure.

Core Problems It Solves

  • Sensitive DLP in text and vision prompts
  • Prompt injection and jailbreak attacks
  • Runaway LLM costs
  • Compliance risks (GDPR, HIPAA, PCI-DSS, EU AI Act)
  • Vendor lock-in across evolving model providers

Key Features

  • Multi-Modal PII Redaction โ€” Detects and redacts 30+ entity types in text + vision OCR for images
  • Prompt Injection Protection โ€” Blocks malicious inputs in real time
  • Smart Autonomous Routing โ€” 600+models, 8 providers
  • Budget Enforcement โ€” Hard per-project caps, pre-flight checks, and token quotas
  • Zero Data Retention โ€” Fully stateless; prompts and responses exist only in volatile processing memory.
  • BYOK (Bring Your Own Key) โ€” Pro plan with 0% markup on your provider keys
  • *Kills agent retry loops * โ€” SHA-256 fingerprint detection stops runaway LangChain/CrewAI/AutoGPT loops
  • *Semantic caching *โ€” identical DLP-cleaned prompts return cached responses.
  • *Webhook alerts *โ€” HMAC-signed push notifications for PII blocks, injection attempts, budget exhaustion, and loop detection.
  • *SAML SSO *
  • *4-tier RBAC *
  • *SIEM Connectors *
  • *Hybrid VPC Deployment *
  • EU AI Act Article 12 audit trails โ€” hash-chained, tamper-evident records.
  • *MCP Gateway (private beta) *โ€” DLP firewall for Model Context Protocol tool calls
  • 1M Free Credits on signup โ€” no credit card required

Deploy

Self-host the open-source core (Apache 2.0) or managed cloud service or Hybrid VPC. Change two lines of code (base URL + API key) to route through AISG. No SDK changes, no code refactoring.

Try it free: aisecuritygateway.ai Open source: github.com/aisecuritygateway

  • @imqueue Landing page
    Landing page //
    2026-07-26

AI Security Gateway features and specs

  • PII Detection & Redaction
    28+ entity types (emails, SSN, API keys, etc.)
  • Multi-Modal DLP
    Text + OCR-based image scanning
  • Prompt Injection Detection
    Pattern + heuristic-based filtering
  • Stateless Processing
    No prompt/response storage
  • Smart Model Routing
    Cheapest/fastest model selection
  • Multi-Provider Support
    OpenAI, Claude, Gemini, Groq, MistralAI, Together.AI, DeepInfra
  • Budget Enforcement
    Block or downgrade based on cost thresholds
  • OpenAI-Compatible API
    Drop-in replacement
  • BYOK (Bring Your Own Key)
    Use your own provider credentials
  • Managed Wallet Mode
    Prepaid credits for simplified billing
  • Low Latency
    <50ms for text DLP
  • Audit Logs (Metadata Only)
    Violation types, counts, latency
  • Project-Based Isolation
    Per-key policies and configs
  • Recursive Loop Protection
    SHA-256 fingerprint detection kills agent retry loops
  • Webhook Notifications
    HMAC-signed real-time alerts to Slack/PagerDuty/SIEM
  • EU AI Act Compliance Logging
    Hash-chained tamper-evident audit records
  • Python SDK
    pip install aisg โ€” typed exceptions
  • Chain Verification API
    Verify tamper-evidence of audit trail
  • JSONL Audit Export
    Export compliance records for regulators

@imqueue features and specs

  • TypeScript-first design
    imqueue is built with TypeScript at its core, providing strong typing, better IDE support, and compile-time error checking, which helps catch bugs early and improves the developer experience when building microservices.
  • RPC-style messaging abstraction
    It simplifies inter-service communication by abstracting away the complexities of message queue protocols, allowing developers to make calls that feel like local function calls while the underlying complexity of message passing is handled by the framework.
  • Built on RabbitMQ
    By leveraging RabbitMQ as its message broker, imqueue benefits from a mature, battle-tested messaging system with reliable delivery guarantees, clustering support, and a large ecosystem of tools and documentation.
  • Code generation and tooling
    imqueue provides CLI tools and code generation capabilities that can automatically create service clients and boilerplate code, reducing repetitive work and helping maintain consistency across microservices.
  • Microservices-focused architecture
    The framework is specifically designed for building distributed microservices systems, offering features like service discovery and structured communication patterns that address common challenges in distributed system design.

Possible disadvantages of @imqueue

  • Smaller community and ecosystem
    Compared to more mainstream microservices frameworks, imqueue has a relatively small user base and community, which can mean fewer third-party resources, tutorials, Stack Overflow answers, and community-contributed plugins or extensions.
  • Limited documentation depth
    While basic documentation exists, some users report that advanced use cases, edge cases, and troubleshooting guides are not as thoroughly documented as more established frameworks, requiring more trial-and-error or direct code inspection.
  • RabbitMQ dependency lock-in
    Being tightly coupled to RabbitMQ means teams must adopt and manage this specific message broker, which could be a limitation for organizations that prefer or already use alternative messaging systems like Kafka, NATS, or AWS SQS.
  • Learning curve for framework-specific patterns
    Developers need to learn imqueue's specific conventions, decorators, and architectural patterns, which adds an additional learning curve on top of understanding TypeScript and general microservices concepts.
  • Potential scalability concerns for very large systems
    As with many queue-based RPC frameworks, extremely high-throughput or very large-scale distributed systems may encounter performance bottlenecks or require significant additional configuration and tuning of the underlying RabbitMQ infrastructure.

Analysis of AI Security Gateway

Overall verdict

  • Based on its positioning as an AI security gateway solution, it appears to be a specialized tool aimed at helping organizations secure their AI/LLM deployments, though independent verification of specific claims and performance is recommended before adoption.

Why this product is good

  • Focuses on the growing need for AI-specific security controls as organizations adopt LLMs and AI systems
  • Likely provides centralized monitoring and policy enforcement for AI traffic and interactions
  • May help address emerging risks like prompt injection, data leakage, and unauthorized AI usage
  • Positions itself in a specialized niche addressing modern AI infrastructure security gaps

Recommended for

  • Organizations deploying multiple AI models or LLMs that need centralized security oversight
  • Enterprises concerned about data leakage through AI/LLM interactions
  • Security teams looking to implement guardrails for AI usage across their organization
  • Companies needing to demonstrate AI governance and compliance for regulatory purposes
  • Businesses integrating third-party AI APIs who want an additional security layer

AI Security Gateway videos

+ Add

AI Security Gateway - The AI Firewall. Stop Data Leaks & Slash LLM Costs in 3 Minutes

@imqueue videos

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Category Popularity

0-100% (relative to AI Security Gateway and @imqueue)

AI Security Gateway

@imqueue

AI
100 100%
AI
0% 0
Realtime Backend / API
0 0%
Realtime Backend / API
100% 100
Security & Privacy
100 100%
Security & Privacy
0% 0
Developer Tools
58 58%
Developer Tools
42% 42

Questions & Answers

As answered by people managing AI Security Gateway and @imqueue.

Why should a person choose your product over its competitors?

AI Security Gateway's answer

AI Security Gateway offers a unique combination that no competitor matches:

  • vs. Portkey/Helicone: They observe and log. We actively redact PII, kill agent loops, and push webhook alerts โ€” before your data leaves your infrastructure.
  • vs. OpenRouter: They route traffic. We govern it โ€” with PII redaction, budget enforcement, loop protection, and EU AI Act compliant audit trails.
  • vs. Vercel AI Gateway: They passively log. We scan, redact, block, and alert in real time.
  • vs. LiteLLM: We add a built-in firewall, webhook notifications, compliance logging, and managed hosting.

Plus: EU AI Act Article 12 enforcement begins August 2, 2026. AISG ships compliant audit trails today โ€” hash-chained, tamper-evident, with JSONL export and chain verification. Most competitors have no compliance story at all.

How would you describe the primary audience of your product?

AI Security Gateway's answer

Software Architects, CISOs, and Engineering Managers at organizations moving LLM implementations from "experimentation" to "production." We serve teams that need to satisfy strict security and compliance reviews while simultaneously reducing the high cost of proprietary AI models. AI Security gateway is designed for developers, startups, and enterprises building applications with LLMs. It is especially valuable for teams moving from experimentation to production, where concerns around data security, compliance, and cost control become critical.

Which are the primary technologies used for building your product?

AI Security Gateway's answer

AI Security Gateway is built using a cloud-native architecture with Python-based API services, containerized deployments (ECS/EKS), and AWS infrastructure components such as NoSQL Databases and CDN. It leverages industry-standard NLP and security frameworks for detection and integrates with multiple LLM provider APIs through a unified, controlled and optimized gateway layer.

Who are some of the biggest customers of your product?

AI Security Gateway's answer

AI Security Gateway is currently being adopted by early-stage startups, independent developers, and AI-focused teams experimenting with production use cases. As the platform evolves, it is designed to support enterprise-grade deployments with advanced governance and compliance requirements.

What's the story behind your product?

AI Security Gateway's answer

AI Security Gateway (AISG) was built after observing a recurring pattern across teams adopting LLMs: developers were unknowingly sending sensitive data such as API keys, logs, and customer information directly to external AI providers, while also struggling with unpredictable costs. Existing solutions either focused on routing or security, but not both. AISG was created as a unified layer to solve these real-world problems โ€” enabling safe, controlled, and cost-efficient AI adoption. AISG was born out of a realization by its founder, a veteran software architect, that 'Shadow AI' was becoming the biggest security risk in the modern stack. After seeing users accidentally paste company secrets into AI prompts, we engineered a stateless, high-performance firewall to allow innovation to continue without compromising data sovereignty.

What makes your product unique?

AI Security Gateway's answer

Unlike standard AI gateways that act as passive proxies, AI Security Gateway is an active security and compliance engine. We combine:

  1. Multi-modal Vision DLP โ€” OCR scans images for PII before they reach any provider
  2. Recursive Loop Protection โ€” the only API proxy that detects and kills agent retry loops at the gateway layer, across all frameworks (LangChain, CrewAI, AutoGPT)
  3. Real-time Webhook Alerts โ€” HMAC-SHA256 signed push notifications to your SOC workflow. Most AI proxies require polling; AISG pushes events the moment they happen.
  4. EU AI Act Compliance โ€” hash-chained, tamper-evident audit records that satisfy Article 12 requirements. SHA-256 fingerprints only โ€” no raw content stored. Privacy by design.
  5. Financial Intelligence โ€” treats LLM tokens like a trading desk, routing each request to the cheapest provider in real time. All in a single stateless proxy with 2-line integration

User comments

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Social recommendations and mentions

Based on our record, AI Security Gateway seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AI Security Gateway mentions (1)

  • I Built an Open-Source AI Firewall Because Every LLM App Leaks Data
    I built AI Security Gateway to fix this. It's an open-source proxy that sits between your app and any LLM provider. Every prompt passes through a security layer before it reaches the model. - Source: dev.to / 3 months ago

@imqueue mentions (0)

We have not tracked any mentions of @imqueue yet. Tracking of @imqueue recommendations started around Jul 2026.

What are some alternatives?

When comparing AI Security Gateway and @imqueue, you can also consider the following products

Portkey - Build production-grade & reliable AI apps with Portkey

Anypoint MQ - With Anypoint MQ, perform advanced asynchronous messaging scenarios โ€” such as queueing and pub/sub โ€” with hosted and managed cloud message queues and exchanges.

liteLLM - One library to standardize all LLM APIs

NSQ - A realtime distributed messaging platform.

OpenRouter - A router for LLMs and other AI models

Helicone AI - Open-source LLM Observability for Developers

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