Software Alternatives, Accelerators & Startups

Hellomatik VS @imqueue

Compare Hellomatik VS @imqueue and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Hellomatik logo Hellomatik

The AI agent platform for the whole company: agents that answer customers, sell and execute real operations across departments, with a human in the loop. One license, unlimited users.

@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.
Not present

Hellomatik is an AI agent platform that puts a whole company's knowledge to work. You build department-specific agents grounded in your real systems and documents that answer customers 24/7, assist and close sales, and run operational workflows across your channels, always with a human in the loop for control. It ships as one company license with unlimited users and pay-for-real-use pricing, so cost doesn't scale with headcount. Teams use it for customer support, assisted selling, management reporting, staff training, quote generation and invoice collection, connecting the tools they already use: WhatsApp, Gmail, Google Drive, Shopify, WooCommerce, Meta Ads, Stripe and SQL databases. A startup from Spain, available in English and Spanish.

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

Hellomatik

$ Details
paid
Release Date
2025 July
Startup details
Country
Spain
State
Madrid
Founder(s)
Isaac Correa, Daniel Correa
Employees
1 - 9

Hellomatik features and specs

  • Multichannel customer answers
    Agents answer customer questions across voice, chat and WhatsApp.
  • Appointment booking
    Book and manage appointments for clinics, after-hours included.
  • Lead qualification with human handoff
    Qualify leads and hand off to a human when it matters.
  • Operations execution
    Execute real operations in your existing systems.
  • AI site search
    AI-powered site search for e-commerce catalogs.

@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 Hellomatik

Overall verdict

  • I don't have verified, up-to-date information about Hellomatik (hellomatik.com) to make a reliable assessment of its quality, so I can't confidently say whether it is good or not.

Why this product is good

  • I don't have specific data on this platform's features, pricing, or user reviews
  • No verifiable information is available to me about its reliability, customer support, or track record
  • Without firsthand or documented evidence, any claims about its quality would be speculative

Recommended for

  • Anyone considering this service should check recent user reviews on independent platforms
  • Look for information on trust/scam-check sites (e.g., Trustpilot, BBB, Reddit discussions)
  • Verify company registration, contact details, and terms of service directly on the site before committing
  • Consider reaching out to existing customers or communities familiar with the product for firsthand feedback

Category Popularity

0-100% (relative to Hellomatik and @imqueue)
AI Chatbots
100 100%
0% 0
Realtime Backend / API
0 0%
100% 100
AI
100 100%
0% 0
Developer Tools
0 0%
100% 100

Questions & Answers

As answered by people managing Hellomatik and @imqueue.

What makes your product unique?

Hellomatik's answer

Hellomatik transforms businesses into self-operating systems. Unlike traditional automation tools that connect apps, Hellomatik builds agentic workflows โ€” AI agents that understand context, make decisions, and execute actions across channels (voice, chat, email, WhatsApp). It doesnโ€™t just respond; it acts. Each module (Voice, Chat, Support, Procedures) runs on a shared โ€œCerebroโ€ that learns from real data and procedures, turning company knowledge into operational intelligence.

Why should a person choose your product over its competitors?

Hellomatik's answer

Because Hellomatik replaces fragmentation with coherence. Where others offer bots or isolated automations, Hellomatik acts as a single operating layer for the entire company โ€” centralizing knowledge, workflows, and actions under one interface. It executes real work: answering calls, booking appointments, running campaigns, resolving issues, and documenting every step. The result is measurable autonomy, not just convenience.

How would you describe the primary audience of your product?

Hellomatik's answer

Mid-to-large organizations that want to scale operations without adding human overhead โ€” especially in industries like healthcare, retail, logistics, and manufacturing. Teams that already use CRMs, ERPs, or scheduling systems but want them to think and act together through AI-driven workflows.

What's the story behind your product?

Hellomatik's answer

Hellomatik was born from frustration โ€” the founder realized his company only functioned when he was there. Every email, call, and report depended on him. The question became: what if a business could run itself? That idea evolved into Hellomatik: a system that gives companies memory, reasoning, and action โ€” so they mature, learn, and operate without constant supervision. Itโ€™s not just automation; itโ€™s operational intelligence.

Which are the primary technologies used for building your product?

Hellomatik's answer

Python, Node.js, React, PostgreSQL, Docker, Vapi.ai (for voice), ElevenLabs (speech synthesis), OpenAI APIs (LLM reasoning and retrieval), and custom RAG infrastructure for enterprise knowledge. All orchestrated under a modular architecture with Spaces, Memory, and Workflows.

User comments

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