Google Cloud has launched Vertex AI Agent Builder, an incredible tool that not only simplifies the process of building advanced AI agents but also assists them to understand and interpret complex data sets. The model aims to connect the development of AI models and the deployment into production environments. This powerful tool can be used both by beginners and advanced developers.
On Tuesday at Google Cloud Next event, the company introduced a tool to help companies build AI agents.
“Vertex AI Agent Builder allows people to very easily and quickly build conversational agents,” Google Cloud CEO Thomas Kurian said. “You can build and deploy production-ready, generative AI-powered conversational agents and instruct and guide them the same way that you do humans to improve the quality and correctness of answers from models.”
The current no-code tool is based on the Gemini large language models of the company and enables a combination of RAG APIs and vector search methods that helps machines to prevent hallucinations where a machine is out of true facts and makes up non-existent answers when it cannot find the correct one.
What is Vertex AI Agent Builder
Vertex AI Agent Builder is an amazing tool that lets developers easily build and deploy enterprise-ready gen AI experiences via a range of tools for different developer needs and levels of expertise, from a no-code console for building AI agents using natural language, to open-source frameworks like LlangChain on Vertex AI.
Additionally, Vertex AI Agent Builder streamlines the process of grounding generative AI outputs in enterprise data. It offers not only Vertex AI Search as an out-of-the-box grounding system, but also RAG (or retrieval augmented generation) APIs for document layout processing, ranking, retrieval, and performing checks on grounding outputs
Key Features and Benefits
1. Accessible for All Levels of Expertise
No-Code Console: Vertex AI comes with agents builder for developers who prefer No-Code Console. With this console you put AI agents to work in a single sentence – create them and deploy using the natural language at hand. Be it a mastered pro or beginner, this user-friendly interface is tailor-made to your budget.
Open-Source Frameworks: For users who want more control, our Vertex AI Agent Builder now supports open-source frameworks, like LlangChain on Vertex AI as well. This flexibility enables software engineers to tailor things to their exact needs despite enjoying the perks of having a user-friendly feature.
2. Grounding Generative AI Outputs
Vertex AI Search: Unlike several AI grounding systems, this AI Agent Builder delivers AI results firmly based on enterprise data. A critical aspect of a personalization system is keeping the information precise and significant.
Retrieval Augmented Generation (RAG) APIs: These APIs are in place for managing the layout of documents, ranking, and picking up documents as well as the check for grounding outputs. These agents help in brushing up the difference between natural AI and real-world scenarios.
3. Enhanced Model Responses
Vector Search: The developers can construct vector search-based agents using embedding. Embedding enables uncertainty reduction and intervention model responses become more precise and relevant. It answers customers’ requests or assists with internal activities as well, and this permits the system’s user interface to be more easily understood.
4. Security and Governance
Built-In Security: Agent Builder, the AI product from Vertex security, is number one. The new enterprise version empowers businesses with the opportunity to flawlessly implement the production-ready security controls feature within the AI-powered generative tools.
Also Explore: Best AI Agents – 2024
How is Vertex AI Different from its Competitors?
| Feature | Google Vertex AI | AWS Sagemaker | Amazon Bedrock |
| Model Support | PaLM2 (Text-Bison) | Falcon-7b-instruct | AI21 Labs Jurassic-2 Mid |
| Use Case Performance | Superior performance in generating medical summaries without extensive coding efforts | Performance varies by use case | Better performance than sagemaker |
| Ease of Use | Designed for ease of use, with a focus on no-code interfaces and simplified development processes | Offers a wide range of tools and services, but may require more extensive coding efforts | Offers a user-friendly interface for generating content without coding efforts |
| Integration with Other Services | Seamless integration with Google Cloud Storage, eliminating the need for network errors | Integrates with a wide range of AWS services, but may require more extensive setup and configuration | Integrates with AWS services, providing a comprehensive ecosystem for AI development |
| Community and Support | Offers a growing community and extensive documentation, but as a newer platform, it may not have as extensive support as more established competitors | Has a large community and extensive documentation, with a long history of support for various AI and machine learning projects | Offers a user-friendly interface and comprehensive documentation, with a focus on ease of use for content generation tasks |
| Scalability | Built-in support for distributed training and can automatically scale up or down based on the needs of your workload | Offers scalability options, but may require more manual configuration | Offers scalability options, with a focus on ease of use for content generation tasks |
Who Signed up Already
The future quest of Vertex AI is to let the agent builder be set free in many business areas. Several organisations have already started utilising the power of Vertex AI Agent Builder.
ADT: ADT is already building a smart assistant that will help the 6-million customers to make intelligent decisions on the security systems set-up.
Intercontinental Hotels Group (IHG): IHG aims at unveiling a boosted AI-based travel assistance with a facility to prepare plans for guests to have a pleasant trip.
NewsCorp: News Corp applies Vertex AI to mine data through over 30 thousands information resources from 2.5 billion daily published articles.
Mayo Clinic: Academics at the Mayo Clinic employ Vertex AI Agent Builder to mine the 50 petabytes of clinical data.
Vodafone: Using Vertex AI, a Vodafone tool identifies the commercial terms similar and dissimilar across a large number of contracts through a highly effective and secure manner.
Pricing and Availability
Vertex AI agent builder can be access here. Google is offering, providing one-time credit of $1,000 per Vertex AI Agent Builder account. The credit is applicable up to 12 months post-activation for new customers. Ease of use having been an integral part of this launch, it is expected that more users are going to sign up for it.
Also Read: OpenAI Building AI Agents
Security and Compliance
The act of security and compliance is baked in Vertex AI Agent Builder; hence even a developer who is not a seasoned coder can create AI agents that meet the highest standards. While the platform provides for a full spectrum of compliance and security standards, including HIPAA, ISO 27000-series, SOC-1/2/3, VPC-CMEK, etc The platform supports a range of compliance and security standards. These denominators guarantee that technical workers can be employed on creative tasks while the data is being protected and the services are being run smoothly.
Conclusion
Vertex AI Agent Builder represents a significant step forward in the development of AI agents, offering a comprehensive suite of tools and features designed to simplify the process of creating high-quality AI experiences. By providing a no-code interface, seamless integration with Vertex AI Studio, support for compliance and security standards, and advanced tooling for AI agent development, Vertex AI Agent Builder is set to become an indispensable tool for developers and organisations looking to leverage the power of AI.
