Vertex AI: Create Intelligent Agents with Google’s AI

Vertex AI Agent Builder is a Google Cloud platform designed to create chatbots and artificial intelligence agents, combining guided conversational flows and generative reasoning powered by Gemini 2.5, Google’s most advanced language model. This tool ranks among the best AI solutions for building intelligent and multilingual agents, offering SMEs a secure, flexible and highly scalable environment.

For small and medium enterprises, this type of technology represents a concrete competitive advantage: automated agents reduce operational costs, improve customer service and streamline processes across channels like web, WhatsApp or email. Vertex AI differentiates itself by integrating all these capabilities in a solid infrastructure, with Google Cloud’s backing and corporate-level security standards.

AgentAya Verdict: Vertex AI

This tool is a comprehensive platform for creating chatbots and generative AI agents with a level of customization difficult to match. Its greatest strength lies in native integration with Google Cloud products and in the combination of contextual reasoning and guided flows, ideal for SMEs already operating in this ecosystem. However, its technical approach and variable costs make it less accessible for micro-businesses or very low-budget projects. Still, it’s one of the most complete tools on the market for those seeking multilingual conversational automation and total control over infrastructure.

Final verdict: highly recommendable tool for companies with medium or advanced technical requirements wanting secure and scalable intelligent agents.

Score Breakdown

Category	Score	Description
Features and Functionality	⭐⭐⭐⭐⭐ (5/5)	Combines deterministic flows with generative AI and contextual reasoning
Integrations	⭐⭐⭐⭐⭐ (5/5)	Direct connection with Google Cloud ecosystem and open APIs
Language and Support	⭐⭐⭐⭐ (4/5)	Documentation in multiple languages; localized interface
Ease of Use	⭐⭐⭐ (3/5)	Visual interface with drag-and-drop builder, medium learning curve
Value for Money	⭐⭐⭐ (3/5)	Flexible pricing according to use; high value for scale projects

AgentAya Overall Score: ⭐⭐⭐ 3.4 / 5

Vertex AI stands out for its power and flexibility, with a steeper technical curve but great benefits for companies with complex AI needs.

Main Features

• Visual interface for designing conversations based on connectable blocks (drag-and-drop), where the user creates routes, conditions and intents by dragging and linking elements intuitively, without programming.
• Integration with Gemini models for contextual reasoning, natural language understanding and multimodal generation (text, image, audio or video, depending on model).
• Access to Vertex AI Search and RAG (Retrieval Augmented Generation) (search supported by internal documents). This allows the agent to consult internal databases and documents before responding, offering precise and verifiable results.
• Compatibility with Agent-to-Agent protocols, facilitating collaboration between multiple agents within the same environment or in external frameworks.
• Native integration with BigQuery, Apigee, Cloud Functions, Firebase and over one hundred other Google Cloud services.
• Model library in Model Garden, where you can select, adjust and deploy Google models, third-party or open source.
• Integrated tools for development and operation: Vertex AI Studio (prototyping and testing), Vertex AI Pipelines, Model Registry, Feature Store and Vertex AI Evaluation.

These capabilities allow SMEs to design precise, coherent agents connected to their existing infrastructure, with notable savings in time and resources.

AI Functions

• Gemini models with advanced reasoning and semantic understanding, capable of interpreting multiple data types.
• Combination of predefined flows and generative responses, dynamically adapting to user context.
• Information retrieval through Vertex AI Search and RAG, reinforcing response precision.
• Automatic quality evaluation and prompt comparison to maintain coherence in different scenarios.
• Broad multilingual support, with fluent text understanding and generation in multiple languages.
• Integration of automated actions that allow executing queries, recording information or activating business processes from the agent itself.

Vertex AI stands out because it brings together, in a single platform, latest generation models (Gemini), enterprise search (query your own documents), data (Vertex AI Search and information retrieval techniques) and a set of operational tools ready for production (MLOps). This integration reduces errors, accelerates the path from prototype to production and allows evolving from a basic bot to an agent with true reasoning and quality control, without changing the environment or sacrificing security or compliance.

Integrations

• Connections with BigQuery, Apigee, Cloud Functions, Firebase and Dialogflow to process data, deploy custom logic and manage conversation flows.
• Compatibility with over one hundred tools from Google Cloud ecosystem through connectors and extensions; API and SDK support for custom developments.
• Communication between agents through Agent-to-Agent protocol, coordinating specialized agents without rewriting code.
• Integration with messaging and chat channels: connection to WhatsApp through gateways (for example, Twilio) or via Dialogflow CX with providers; also works on web and mobile applications.
• Integration with databases like AlloyDB or Spanner for predictions and queries near the data.
• Compatibility with enterprise authentication (SSO, IAM) and network security controls for high-demand environments.

Security and Data Compliance

Google Cloud applies enterprise-level security policies. Data processed in Vertex AI remains under client ownership and isn’t used to train AI models without explicit consent. All communication is encrypted using TLS 1.3 in transit and AES-256 at rest.

Vertex AI complies with ISO/IEC 27001, 27017, 27018, SOC 1 and SOC 2 Type 2, plus GDPR and CCPA. Includes multi-factor authentication and access controls through IAM (Role-Based Access Control) and SAML SSO, guaranteeing SME data is protected against unauthorized access.

Language – Customer Support and Interface

Vertex AI’s official documentation is available in multiple languages; additionally, Google Cloud Console and Vertex AI pages can be displayed in various languages according to language preference. In practice, most of the interface is localized, though certain sections or messages may appear in English. Google Cloud Customer Care offers support in multiple languages. Available language and schedule depend on plan and region; there’s coverage in multiple languages through Google Cloud support channels.

AI Language – The Tool Itself

Vertex AI’s generative models support text and voice in over 95 languages, including various European, Asian and international languages. Prompt understanding in multiple languages is excellent thanks to Gemini’s multilingual training, allowing creation of chatbots that interact naturally with international customers without needing intermediate translations.

Mobile Access

There’s no specific mobile application for Vertex AI; however, the web console is designed responsively, allowing supervision and administration of agents from a mobile browser or tablet. Still, more advanced tasks (like integrating and deploying models) are performed with greater comfort and efficiency from desktop equipment.

Vertex AI is a development platform, not a consumer product. What it does is offer the intelligent backend: Gemini models, Vertex AI Search, data storage, flow orchestration, etc. Consequently, you can use these capabilities to create an agent and integrate it into a mobile application, whether Android or iOS.

Support, Onboarding and Account Management

Vertex AI offers complete documentation, interactive code labs (codelabs) and step-by-step tutorials. The onboarding process is supported by Vertex AI Workbench and pre-configured templates. Enterprise plans include access to customer success managers and priority support, while SMEs can rely on free resources and active technical communities.

Ease of Use / UX

The interface is based on Dialogflow CX’s visual environment, with drag-and-drop blocks (visual construction with connectable blocks) and modular intent management.

Although the initial learning curve may be moderate, especially for those not using Google Cloud, the experience is fluid and allows obtaining tangible results in a few hours of configuration.

Pricing and Plans

Vertex AI is part of Google Cloud and is billed per use. There’s no free plan specific to the product; new Google Cloud customers have initial free credits applicable to Vertex AI for a limited time period. To estimate costs, it’s recommended to use the Vertex AI calculator and, if applicable, request a commercial quote.

Case Study

A tourism sector SME implemented Vertex AI Agent Builder to centralize multilingual customer service.

In three months it reduced support email volume by 40% and managed to automate bookings and itinerary changes through an agent connected to its Firebase backend.

The result: less operational load and greater end-user satisfaction, without losing the human touch.

Vertex AI vs Alternatives

Tool	Key Advantages	Main Limitations	Ideal for
Vertex AI	Complete integration with Google Cloud; Gemini models; augmented search (RAG); MLOps tools; security control and regulatory compliance	Higher learning curve; console primarily in English; requires cost planning per use	SMEs and companies already using Google Cloud or needing scalability, data privacy and technical control
Noem AI	Simple configuration; fully visual environment; quick implementation without technical knowledge	Less integration and customization capacity; limited for high-volume projects or complex flows	Entrepreneurs and small teams prioritizing launch speed over technical complexity
StackAI	Quick prototype and proof-of-concept design; no-programming interface; ideal for validating ideas	Not oriented to large enterprise environments; fewer control and compliance tools	SMEs or startups seeking to validate AI use cases before scaling to more robust solutions

FAQs (Frequently Asked Questions)

Is Vertex AI good for SMEs? 

Yes, especially for SMEs with certain digital maturity or Cloud infrastructure. Offers scalability and customization, though its complexity may be high for beginners.

Does it support multiple languages? 

Yes. Gemini models understand and generate text in multiple languages with high precision, and documentation is available in various languages.

What are the best alternatives to Vertex AI? 

Noem AI and Stack AI are more accessible alternatives with no-code interfaces, suitable for startups and small teams.