What I like most about Lyzr.ai is its focus on building production-ready AI agents rather than just AI demos. The platform's emphasis on secure, enterprise-grade AI, built-in safety features, and support for multi-agent workflows makes it practical for solving real business problems. I also like that it simplifies the development process with low-code tools, RAG capabilities, and integrations with multiple LLMs, allowing developers to build and deploy AI applications much faster. As someone interested in AI/ML engineering, I find Lyzr's focus on scalable, responsible AI and real-world deployment especially appealing. Review collected by and hosted on G2.com.

One area I think could be improved is the learning curve for new users. Since Lyzr.ai offers many advanced capabilities, beginners may need more guided tutorials, end-to-end examples, and documentation to get productive quickly. Expanding the educational resources and sample projects would make the platform even more accessible while maintaining its powerful feature set. Review collected by and hosted on G2.com.

What I like most about Lyzr.ai is how simple it makes building AI Agents. I've been using it for over a year and have built few projects while learning through their workshops and the Architect Demo Day in Bengaluru. I especially like that I can quickly turn an idea into something working without spending too much time on setup. Review collected by and hosted on G2.com.

The platform is easy to use overall, but some advanced features take a little time to understand if you're new. I would also like see more ready to use templates and real world project examples(except the common and basic ones) to make getting started even easier. Review collected by and hosted on G2.com.

Well, to be honest, the fact I like best about Lyzr.ai is how quickly it lets you build and test AI agents without having to develop the entire orchestration layer from scratch.

During my evaluation phase, I was able to create agent workflows, configure prompts, and connect them to external data sources through an intuitive interface.

The platform itself made it easy to iterate on different workflows and compare results without spending excessive time on infrastructure.

I also appreciated the modular design, which made it straightforward to experiment with different agent behaviours and refine them based on the output.

For rapid prototyping and proof-of-concept development, it significantly reduced development time while still providing enough flexibility for more advanced use cases.

These are the best features. Review collected by and hosted on G2.com.

I would have very well said: Nothing. lol. However, while Lyzr.ai is easy to get started with, I found that building more sophisticated multi-agent workflows required some experimentation.

Certain advanced configuration options were not immediately obvious, so I relied on the documentation and trial-and-error to achieve the desired behavior.

I also think the platform could benefit from more comprehensive tutorials, real-world implementation examples, and a wider range of native integrations with enterprise applications.

Better debugging and observability tools for understanding why an agent made a particular decision would also make troubleshooting complex workflows easier. Review collected by and hosted on G2.com.

I use Lyzr.ai for building sophisticated billing agents, multi-agent systems, and creating complex automations. It helps with quick agent development, especially using NLP-based prompts, which makes it quite useful. The agent studio is a feature I particularly like, as it lets me customize and build high-scale, production-grade agents more easily. I enjoy how Lyzr.ai allows for enhancements and makes recommendations that improve my workflow. The setup process was straightforward and easy, which made it simple for tech developers to get started. Review collected by and hosted on G2.com.

The main area for improvement is that it takes a bit more time than expected. I think latency should be reduced for better performance. It could also improve in terms of recommendations on scaling and improvising tasks. Having suggestions from an architect or insights into how to enhance tasks would be great. More improvisations in the capabilities of the agent studio would also be beneficial. Review collected by and hosted on G2.com.

I like the ease of use of Lyzr.ai. The architect product is really helpful as it allows me to plan the product first, discuss execution, and specify the agents and orchestration needed. It's great for building a proof of concept, and I can improve on it with further iterations. I also appreciate that product links are provided for easy sharing with the team, and there are multiple other integrations. Setting it up was very easy; just log in, start the conversation, discuss, and implement-very easy. Review collected by and hosted on G2.com.

The cost is quite high, and the token usage is quite a lot. I need to understand and/or optimize for the tokens. Also, if there was an IDE within the Architect, it would be easier for me to code/text then and there with specific inputs. Review collected by and hosted on G2.com.

I like Lyzr.ai for agentic building and the workflow canvas for building and creating things. The canvas lets me see where the agent failed and observe those steps, which is really helpful. Lyzr.ai also makes it easy to build and use AI workflows, which is great for integrating AI into my software. Review collected by and hosted on G2.com.

I find that it consumes a lot of credits, and I think integrating some tasks via GitHub would make it more efficient. It would be great if Lyzr.ai could be called when tasks are completed. Review collected by and hosted on G2.com.

I like that I am not tied to any particular LLM. I can use any LLM of my choice and connect to agents on any cloud platform. Review collected by and hosted on G2.com.

The one thing that I think can be improved is that there is a ton of information and features that Lyzr has and sometimes one can get confused as to where to begin. But I guess that can be solved by "Talk to us" feature. Review collected by and hosted on G2.com.

I really like how easy and fast it is to build and deploy enterprise-grade AI agents without complex coding Review collected by and hosted on G2.com.

The platform’s documentation doesn’t provide clear, up-to-date guidance for more complex setups, which ends up making the advanced onboarding process take longer than I expected. Review collected by and hosted on G2.com.

Lyzer.ai is easy to implement, even for users without a technical background. The interface is intuitive, and creating AI agents does not involve complex setup or coding. Most core features can be used quickly with minimal learning time, allowing users to start building and testing agents almost immediately.

It offers access to many leading AI models, allowing users to choose the best option based on their specific use case. With a wide variety of tools available for seamless agent integration, Lyzer.ai also supports users who are new to generative AI by helping improve prompts and workflows. Overall, Lyzer.ai stands out as one of the best AI studios available today, combining simplicity, flexibility, and powerful capabilities in one platform. Review collected by and hosted on G2.com.

While integrating tools with Lyzer agent or generating outputs like images can sometimes be a bit tricky. It takes some effort to fully understand these features, and agents often need longer testing cycles to work as expected. With the current limit of 500 credits, it can be challenging to experiment with and test multiple agents thoroughly.

The platform is well suited for regular use due to its flexibility, access to multiple leading AI models, and wide range of tools. However, limited credits can make frequent experimentation challenging. Providing bonus credits for active users or introductory discounts would encourage more consistent and long-term usage. Review collected by and hosted on G2.com.

This platform is easy to use. Creating agents, workflows for agentic, setting up custom instructions, and attaching tools to an agent are all quick and reliable processes. The entire setup, testing, and deployment using the API Endpoint is straightforward and efficient. Review collected by and hosted on G2.com.

There is a noticeable lack of integrations, and it would be fantastic if there were an option to create a white-label front end. This would allow non-technical users on a single platform to build their own products, such as with lyzr.ai. Since it already functions as agents on the backend, adding a user interface layer would be an excellent improvement. Review collected by and hosted on G2.com.