--- title: LobeChat Reviews meta_title: 'LobeChat Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 16 reviews by the users' company size, role or industry to find out how LobeChat works for a business like yours. aggregate_rating: rating_value: 4.2 review_count: 16 scale: '5' date_modified: '2026-07-17' parent_category: name: Conversational Intelligence url: https://www.g2.com/categories/conversational-intelligence --- # LobeChat Reviews **Vendor:** LobeChat **Category:** [Chatbots Software](https://www.g2.com/categories/chatbots) **Average Rating:** 4.2/5.0 **Total Reviews:** 16 ## About LobeChat LobeChat - An open-source, modern-design ChatGPT/LLMs UI/Framework. Supports speech-synthesis, multi-modal, and extensible plugin system. One-click \*\*FREE\*\* deployment of your private OpenAI ChatGPT/Claude/Gemini/Groq/Ollama chat application. Features ### 1. Multi-Model Service Provider Support In the continuous development of LobeChat, we deeply understand the importance of diversity in model service providers for meeting the needs of the community when providing AI conversation services. Therefore, we have expanded our support to multiple model service providers, rather than being limited to a single one, in order to offer users a more diverse and rich selection of conversations. In this way, LobeChat can more flexibly adapt to the needs of different users, while also providing developers with a wider range of choices. #### Supported Model Service Providers We have implemented support for the following model service providers: - \*\*AWS Bedrock\*\*: Integrated with AWS Bedrock service, supporting models such as \*\*Claude / LLama2\*\*, providing powerful natural language processing capabilities. - \*\*Anthropic (Claude)\*\*: Accessed Anthropic's \*\*Claude\*\* series models, including Claude 3 and Claude 2, with breakthroughs in multi-modal capabilities and extended context, setting a new industry benchmark. - \*\*Google AI (Gemini Pro, Gemini Vision)\*\*: Access to Google's \*\*Gemini\*\* series models, including Gemini and Gemini Pro, to support advanced language understanding and generation. - \*\*ChatGLM\*\*: Added the \*\*ChatGLM\*\* series models from Zhipuai (GLM-4/GLM-4-vision/GLM-3-turbo), providing users with another efficient conversation model choice. - \*\*Moonshot AI (Dark Side of the Moon)\*\*: Integrated with the Moonshot series models, an innovative AI startup from China, aiming to provide deeper conversation understanding. - \*\*Groq\*\*: Accessed Groq's AI models, efficiently processing message sequences and generating responses, capable of multi-turn dialogues and single-interaction tasks. - \*\*OpenRouter\*\*: Supports routing of models including \*\*Claude 3\*\*, \*\*Gemma\*\*, \*\*Mistral\*\*, \*\*Llama2\*\* and \*\*Cohere\*\*, with intelligent routing optimization to improve usage efficiency, open and flexible. - \*\*01.AI (Yi Model)\*\*: Integrated the 01.AI models, with series of APIs featuring fast inference speed, which not only shortened the processing time, but also maintained excellent model performance. ### 2. Local Large Language Model (LLM) Support To meet the specific needs of users, LobeChat also supports the use of local models based on Ollama, allowing users to flexibly use their own or third-party models. ### 3. Model Visual Recognition LobeChat now supports OpenAI's latest model with visual recognition capabilities, a multimodal intelligence that can perceive visuals. Users can easily upload or drag and drop images into the dialogue box, and the agent will be able to recognize the content of the images and engage in intelligent conversation based on this, creating smarter and more diversified chat scenarios. This feature opens up new interactive methods, allowing communication to transcend text and include a wealth of visual elements. Whether it's sharing images in daily use or interpreting images within specific industries, the agent provides an outstanding conversational experience. ### 4. TTS & STT Voice Conversation LobeChat supports Text-to-Speech (TTS) and Speech-to-Text (STT) technologies, enabling our application to convert text messages into clear voice outputs, allowing users to interact with our conversational agent as if they were talking to a real person. Users can choose from a variety of voices to pair with the agent. Moreover, TTS offers an excellent solution for those who prefer auditory learning or desire to receive information while busy. In LobeChat, we have meticulously selected a range of high-quality voice options (OpenAI Audio, Microsoft Edge Speech) to meet the needs of users from different regions and cultural backgrounds. Users can choose the voice that suits their personal preferences or specific scenarios, resulting in a personalized communication experience. ### 5. Text to Image Generation With support for the latest text-to-image generation technology, LobeChat now allows users to invoke image creation tools directly within conversations with the agent. By leveraging the capabilities of AI tools such as DALL-E 3, MidJourney, and Pollinations, the agents are now equipped to transform your ideas into images. This enables a more private and immersive creative process, allowing for the seamless integration of visual storytelling into your personal dialogue with the agent. ### 6. Plugin System (Function Calling) The plugin ecosystem of LobeChat is an important extension of its core functionality, greatly enhancing the practicality and flexibility of the LobeChat assistant. By utilizing plugins, LobeChat assistants can obtain and process real-time information, such as searching for web information and providing users with instant and relevant news. In addition, these plugins are not limited to news aggregation, but can also extend to other practical functions, such as quickly searching documents, generating images, obtaining data from various platforms like Bilibili, Steam, and interacting with various third-party services. ### 7. Agent Market (GPTs) In LobeChat Agent Marketplace, creators can discover a vibrant and innovative community that brings together a multitude of well-designed agents, which not only play an important role in work scenarios but also offer great convenience in learning processes. Our marketplace is not just a showcase platform but also a collaborative space. Here, everyone can contribute their wisdom and share the agents they have developed. ### 8. Mobile Device Adaptation We have carried out a series of optimization designs for mobile devices to enhance the user's mobile experience. Currently, we are iterating on the mobile user experience to achieve smoother and more intuitive interactions. If you have any suggestions or ideas, we welcome you to provide feedback through GitHub Issues or Pull Requests. ### What's more Beside these features, LobeChat also have much better basic technique underground: - [x] \*\*Quick Deployment\*\*: Using the Vercel platform or docker image, you can deploy with just one click and complete the process within 1 minute without any complex configuration. - [x] \*\*Custom Domain\*\*: If users have their own domain, they can bind it to the platform for quick access to the dialogue agent from anywhere. - [x] \*\*Privacy Protection\*\*: All data is stored locally in the user's browser, ensuring user privacy. - [x] \*\*Exquisite UI Design\*\*: With a carefully designed interface, it offers an elegant appearance and smooth interaction. It supports light and dark themes and is mobile-friendly. PWA support provides a more native-like experience. - [x] \*\*Smooth Conversation Experience\*\*: Fluid responses ensure a smooth conversation experience. It fully supports Markdown rendering, including code highlighting, LaTex formulas, Mermaid flowcharts, and more. More features will be added when LobeChat evolves ## LobeChat Pros & Cons **What users like:** - Users find LobeChat's **easy setup** ideal for enhancing content and deploying chatbots effortlessly. (3 reviews) - Users appreciate the **ease of use** of LobeChat, finding it simple to build chatbots without technical skills. (2 reviews) - Users value the **seamless integrations** of LobeChat, enhancing their workflows and overall productivity. (2 reviews) - Users appreciate the **various customization options** in LobeChat, enhancing their experience and interface usability. (1 reviews) - Users love the **ease of understanding** with LobeChat, finding it effortless to build chatbots without technical skills. (1 reviews) - Features (1 reviews) - Scheduling Posts (1 reviews) - Time-saving (1 reviews) - User Interface (1 reviews) **What users dislike:** - Users note the **limited features** of LobeChat, particularly its lack of multilingual support and high pricing for small businesses. (2 reviews) - Users experience **communication issues** , including limited tool integration and delays in support responses. (1 reviews) - Users find the **cost prohibitive** for small businesses due to its numerous limitations and pricing structure. (1 reviews) - Users find the **inefficient reporting** in LobeChat hinders clarity and consistency in responses, affecting their overall experience. (1 reviews) - Users face **integration issues** with limited tool availability and experience delays in support response times. (1 reviews) - Poor Navigation (1 reviews) - Slow Loading (1 reviews) - Unclear Understanding (1 reviews) ## LobeChat Reviews ### 1. One Interface to Switch Models, Agents, Plugins, and Knowledge Base—Self-Hosted Done Right **Rating:** 4.0/5.0 stars **Reviewed by:** Luca P. | Chief Operations Officer DEQUA Studio | Formerly CTO in MarTech, Marketing and Advertising, Mid-Market (51-1000 emp.) **Reviewed Date:** June 18, 2026 **What do you like best about LobeChat?** The model switcher is the part I touch every working day. I run LobeChat self-hosted with my own provider keys, and a dropdown at the top of the conversation lets me move between OpenAI, Claude, Gemini, and a local model running through Ollama without leaving the thread I am in. The practical effect is that I draft with a cheap, fast model and then switch to a stronger one for the pass that actually matters, all inside the same conversation. I stopped paying for three separate chat subscriptions and keeping three browser tabs open to compare them. One interface, my keys, and whichever model fits the task in front of me. The agent marketplace earned its place faster than I expected. I can install a pre-built assistant, fork it, change its system prompt and its default model, and save it under a name that means something to me. I keep a small library of these: a code-review agent pinned to a stronger model, a quick-rewrite agent sitting on something cheap, a SQL helper with the table context already baked into its prompt. Rather than pasting the same three-paragraph system prompt every time I want a particular behavior, I pick the agent and start typing. The marketplace itself is a reasonable starting point, but the real value for me is treating those community agents as templates I bend to my own work instead of building each one from a blank page. Plugins and the MCP marketplace are useful, with a caveat I will get to. The plugin system runs on function calling, so an agent can reach out to a tool mid-conversation to pull a document, hit an API, or generate an image. The MCP marketplace integration matters more to me than the older plugin catalog, because it means I can point LobeChat at the same MCP servers I already use elsewhere rather than waiting for someone to ship a bespoke plugin. When a tool is wired in correctly, it is the difference between a chat window and something that can actually carry out a step of real work. Not every plugin is maintained to the same standard, which I will come back to in the dislikes, but the handful I depend on are dependable. The knowledge base quietly changed how I use the tool for real work. I upload a set of internal documents, and retrieval pulls the relevant chunks into context when I ask a question, so I am querying our own material instead of pasting it in by hand every time. On the self-hosted server version this rides on Postgres with the pgvector extension, which means the documents and their embeddings sit on infrastructure I control rather than in some third party's store. For anything that touches internal information, that distinction is the entire reason I chose to host it myself. Artifacts and the rendering are a smaller pleasure that adds up over a day. Code comes back in a side panel with proper highlighting, and markdown, Mermaid diagrams, and LaTeX render in place rather than arriving as raw text I have to copy somewhere else to read. When I am working through something that has a diagram or a formula in it, seeing it rendered inline keeps me moving instead of bouncing out to a separate viewer. It is not the feature that sold me, but it is the kind of detail I would miss the moment I went back to a plainer client. Multi-modal input is more useful in practice than I assumed it would be. I can drop an image into a conversation and have a vision-capable model describe or reason about it, generate an image from a prompt when I need a quick visual, and use speech in and out on the occasions when typing is not convenient. None of this is unique to LobeChat taken feature by feature, but having vision, image generation, and voice sitting in the same place as the text models, rather than spread across three more tabs, is what makes me actually use them. A screenshot of a broken layout or an error dialog goes straight into the chat instead of being routed through a separate tool first, which is usually the moment I would have given up and just described it in words. Running local models through Ollama is an option I am glad exists even though I do not reach for it constantly. For a prompt that involves anything I would rather not send to a hosted provider, I switch the conversation to a local model and the request never leaves my own hardware. Having that escape route in the same interface, one dropdown away from the cloud models, means privacy is a per-conversation choice rather than a separate tool I have to remember to open. The interface itself is calm and quick, and it holds up across the desktop app and the browser PWA, including on my phone when I am away from my desk. What makes me comfortable building a workflow on it is that the project keeps moving. It picked up native support for Claude's SKILL.md skills format not long after that standard appeared, which is the sort of thing that tells me the people behind it are tracking where the field is going rather than coasting on what already shipped. **What do you dislike about LobeChat?** The first hour is harder than it should be for anyone non-technical. I handed the tool to a teammate who is not a developer and watched them get lost between agents, plugins, providers, and API keys, none of which they needed to think about to send a first message. The settings run deep, and the surface area you see before you have done anything is larger than the task of "just chat with a model" warrants. The workaround I have settled on is to set people up once myself, with a couple of agents already configured and a sensible default model chosen, so their daily experience is simple even though the initial setup is not something I would leave them to do alone. The jump from the simple deployment to the full self-hosted server version is a real step up in effort. A basic Docker container with local storage is genuinely a few minutes of work. The moment you want the knowledge base, cross-device sync, and persistent accounts, though, you are standing up Postgres with pgvector, a Redis instance, and S3-compatible object storage, and then thinking about backups and secrets for all of it. It is well documented and it does work, but it is a small piece of infrastructure to own rather than a one-click affair, and I would not hand that part to anyone who does not already run services for a living. If you go the hosted route instead of self-hosting, the credit-based pricing is harder to predict than a flat subscription. The cloud plans bill in compute credits tied to token usage, and a heavy day of long contexts and retrieval can burn through them faster than you would guess from the headline number. I evaluated the cloud version before committing and ended up self-hosting partly for this reason, because pay-per-token on my own provider keys at least gives me line-item visibility into where the spend is going. Enterprise controls are lighter than a tool built squarely for large organizations. SSO and OAuth are present, and for a small team that is plenty. Org-level administration and audit logging, though, are thinner than what a compliance team would want to see, so for a regulated environment this is the area to check carefully before standardizing on it. It is a question of intended scale rather than a flaw, but it is worth knowing going in. The last one is a mix of the tool and the models sitting behind it. Every so often a single response will contradict itself or drift from the format I asked for, and a long retrieval query against a large knowledge base adds latency you can feel. A fair amount of that is model behavior rather than anything LobeChat is doing wrong, but it surfaces inside LobeChat so it is part of the day-to-day experience regardless. The plugin ecosystem is also still maturing, and a couple of the plugins I tried early on were plainly unmaintained, so I have learned to stick with the ones that show active upkeep and not assume everything in the catalog still works. **What problems is LobeChat solving and how is that benefiting you?** The core thing it fixed was the sprawl of separate AI tools. Before, I had a ChatGPT subscription, a Claude one, a tab open for Gemini, and a separate flow whenever I wanted a local model, and comparing them meant copying the same prompt into each in turn. Now there is one interface, I bring my own provider keys, and changing model is a dropdown inside the conversation I already have open. The benefit is not only fewer subscriptions to manage. It is that picking the right model for a given task stopped being a context switch and became a single click, which means I actually do it instead of defaulting to whatever was already on screen. Cost control followed directly from that. Routing drafts and throwaway questions to a cheap model, and saving the expensive one for the work that genuinely needs it, is trivial when both live behind the same switcher. Because I am on pay-per-token with my own keys rather than a bundle of fixed monthly plans, I can see what each provider is actually costing me and adjust which model my default agents point at. The spend tracks real usage instead of sitting as a stack of subscriptions I am paying for whether I touch them or not. Keeping sensitive material in-house is the next problem it handles. Between self-hosting the application and being able to run local models through Ollama, prompts and documents that should not leave our network do not have to. The knowledge base storing its embeddings in our own Postgres instance is part of the same picture. For the work where data handling is the constraint, having the whole path stay on infrastructure I control is the difference between being able to use an AI tool for it at all and having to keep that work manual. Standardizing AI access across the team got much easier. Instead of everyone expensing an individual chat subscription and settling on whatever they happened to land on, we run a shared self-hosted instance with central key management, so the available models and the agent library are consistent across the group and I am not chasing reimbursements for a dozen separate personal plans. Onboarding someone to our AI setup now means giving them access to one place that is already configured, not walking them through signing up for three different services. Repeated prompt setups stopped living in my head and a scratch file. The behaviors I reach for again and again are codified as named agents, each with its own system prompt and default model. The before-state was re-pasting a long system prompt and re-selecting the right model every single time I wanted a specific kind of help. The after-state is picking the agent from the list and starting, which sounds minor until you count how many times a day it happens. Querying our own documents in context is the last habit it changed. Rather than pasting a reference document into the prompt by hand, or skimming it myself to find the one paragraph that matters, I ask the question and let retrieval pull the relevant section into the conversation. Because the whole thing is self-hosted, that material stays on our own infrastructure while still being usable in a chat. It turned our internal documents from something I had to manually feed the model into something the model can reach when a question calls for it. Not being tied to one model vendor is a quieter benefit that pays off over time. New models ship at a constant pace, and because LobeChat sits in front of many providers, adopting a new one is a matter of adding a key rather than migrating to a different tool. I am not betting my whole workflow on a single company's roadmap, which, given how quickly this space moves, is worth more than any one feature on the list. ### 2. My brief experience with LobeChat **Rating:** 2.5/5.0 stars **Reviewed by:** Ramraja Y. | Data Analyst, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2024 **What do you like best about LobeChat?** If you are using it for content rewriting to enhance it than it might be a very good product as it might present it in a best possible format due to mix of responses that it uses from other gpts.The setup is definately easy and using it for the research purposes might be a good idea than other gpts. **What do you dislike about LobeChat?** I am not certain why but the response from the gpt seemed slow to me that other gpts and also UI is not that better. The answers sometime might not follow a pattern that they should. I have sometime seen conflicting answers also in a single response that should be looked at **What problems is LobeChat solving and how is that benefiting you?** I had previously used it for generating codes for my data analysis projects, I had found it slow but now as I come back now it has got a lot better specialy in content generation. For research It definately need to be a lot better as the flow of information seem to be missing sometimes. I am currently building a website that writes articles on Data Science and LobeChat might be the best way to write the content that is already in sequence and limits in a way that i want it. I am using it to generate coding question's solutions for the interview preparation for DSA and and analytics for different companies and also correct anamolies in my solutions. ### 3. AIs integration **Rating:** 3.5/5.0 stars **Reviewed by:** Kamakshi S. | Senior Solutions Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** November 26, 2024 **What do you like best about LobeChat?** - It's an integration of commonly used AIs like GPT, Claude, Midjourney, Perplexity etc. Based on your selected and interested topics, Lobe Chat gives you common responses that gives the best recommendation for the specific topics. - Free of use for certain no.of prompts. - You can create knowledge base articles by uploading files and topics - They offer a wide list of plug-ins. Few to generate sample CSV files as well. Instead of using tools like Mockaroo where you provide fields for the sample CSV, you can use the AI prompts to create such files. - The output format is varied ranging from CSV to XML or JSON etc. **What do you dislike about LobeChat?** - The prompt responses are a mix from multiple tools, so the expected outcome is not aligning with the desired result. - The categorization is not helping to that extent since all the categories almost provide similar responses. - The free plan is limited to 500 characters. I don't understand why I have to pay for an AI plug-in tool that only gives responses from Claude and GPT in the paid version, compared to the free version. **What problems is LobeChat solving and how is that benefiting you?** Data dependent solution and responses ### 4. Best LLM platform **Rating:** 5.0/5.0 stars **Reviewed by:** Ujjwal S. | Software Test Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 01, 2024 **What do you like best about LobeChat?** The things I like about lobeChat is easy installation and onboarding process for a beginner. In addition to that the support it provides for API documentation and deployment is appreciable. **What do you dislike about LobeChat?** It's a great software, i didn't find anything about disliking it. **What problems is LobeChat solving and how is that benefiting you?** I have been using it for a while now and one thing that is great about LobeChat is that it has different kinds of chat assistant depending upon the topic. It has helped me in the interview preparation with interview assistant, Frontend and Backend assistant for code deployment, security analyst for security testing scenarios. It has increased the overall productivity and scope of the project of my organisation. ### 5. High Performance, Vision Supported and Extensible Chat Software **Rating:** 4.5/5.0 stars **Reviewed by:** Jasjeet S. | Social Media Marketer, Internet, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2024 **What do you like best about LobeChat?** My experience with LobeChat has been educational and informative. The best thing about LobeChat is its open source high-performance chatbot framework which supports one-click free deployment of private chatgpt like application. **What do you dislike about LobeChat?** I dislike one thing about LobeChat it does not support different languages. The main focus is only given to the English language. **What problems is LobeChat solving and how is that benefiting you?** LobeChat is benefitting to a great extent. This chatbot helped in various marketing aids,offering educational resources, answering questions to my colleagues related to their campaign problems, engaging in conversations and addressing the customers' queries. My business has generated lot of valuable content and it helped my business to generate great ROI. ### 6. Good chat AI assistant for learning or refining prompts **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** June 03, 2025 **What do you like best about LobeChat?** Like the refine prompt feature of Midjourney **What do you dislike about LobeChat?** Its good but i feel it can have a easy interface **What problems is LobeChat solving and how is that benefiting you?** It helps me to refine and fine tune my prompts for image generation, it has other usage also but i use mostly for that ### 7. Great marketplace of assistants, models and plugins **Rating:** 5.0/5.0 stars **Reviewed by:** Ridhima G. | CTO, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2024 **What do you like best about LobeChat?** The best part about using Lobechat is the diverse marketplace, especially for assistants. Some of the assistants are calendar and software architecture assisstant. **What do you dislike about LobeChat?** I feel the onboarding process is somewhat long and confusing. It would be good to have quick onboarding and optional demo for users. **What problems is LobeChat solving and how is that benefiting you?** LobeChat is great for building and using multiple assistants based on the use case. It also has a long list of LLMs so I don't have to roam around get data from various LLMs. ### 8. Great tool for LLM aggregation **Rating:** 5.0/5.0 stars **Reviewed by:** Aarav M. | SWE (Software Engineer), Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2024 **What do you like best about LobeChat?** LobeChat comes with most popular LLMs inbuilt which saves a lot of time as I don't have to use multiple tools again and again. **What do you dislike about LobeChat?** The UI is little cluttered for the first time user. **What problems is LobeChat solving and how is that benefiting you?** One great feature of LobeChat is having marketplace for assisstants. Also, I don't have to go to different solutions like Claude, GPT, etc. LobeChat gives me everything in one place. ### 9. New open sourced AI chatbot **Rating:** 4.5/5.0 stars **Reviewed by:** Stephen William Kay I. | S, Small-Business (50 or fewer emp.) **Reviewed Date:** November 26, 2024 **What do you like best about LobeChat?** I like that it has multimodal capabilities, visual recognition, text-to-speech, has an extensible plugin system and is an open-source framework. it is asl versatie, community driven and has the potential for advanced interactions. **What do you dislike about LobeChat?** The potential downsides are the relative newness and the dependency on AI models. **What problems is LobeChat solving and how is that benefiting you?** The problems lobe chat is solving is offering customization, versatility, and the potential for innovative interactions. ### 10. Great UI and UX **Rating:** 5.0/5.0 stars **Reviewed by:** Keshav M. | Founder and CEO, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2024 **What do you like best about LobeChat?** The overall design of the solution very different from other similar solutions. The onboarding process is very smooth and number of models it support is really great. **What do you dislike about LobeChat?** After the onboarding, it was somewhat difficult to navigate and understand how to get started. **What problems is LobeChat solving and how is that benefiting you?** LobeChat is a great LLM aggregator with support of most modern day LLM tools. ### 11. 10 Days Task in 10 Seconds **Rating:** 5.0/5.0 stars **Reviewed by:** Jerin C. | Human Resources Manager - Shriram Group, Enterprise (> 1000 emp.) **Reviewed Date:** November 30, 2024 **What do you like best about LobeChat?** Excellent GenAI Open source Platform which is very much useful in the day to day task. Build in most recent technology in data science such as LLM Modelling most useful. **What do you dislike about LobeChat?** No I like this product very much and very much helpful in daily task. **What problems is LobeChat solving and how is that benefiting you?** Day to day task on professional life ### 12. Lobechat - a digital guide **Rating:** 4.0/5.0 stars **Reviewed by:** Vaidik P. | Customer Success Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** November 29, 2024 **What do you like best about LobeChat?** Their AI based features and user friendly UI. Their end to end support. **What do you dislike about LobeChat?** They don't provide any AI powered solutions for free just to try. **What problems is LobeChat solving and how is that benefiting you?** Lobechat helps me to provide exact coding for my needs from starting to the completion of project - deployment level ### 13. Wonderful guild for all your AI needs **Rating:** 5.0/5.0 stars **Reviewed by:** Gajalakshme R. | Senior software test engineer, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2024 **What do you like best about LobeChat?** They have a very smooth assistace and chat experience. We can choose a customised user role. The responses are pretty natural. **What do you dislike about LobeChat?** A little lack of understanding is felt some times **What problems is LobeChat solving and how is that benefiting you?** I get to know more about my work and personal needs. ### 14. Good tool for AI search **Rating:** 5.0/5.0 stars **Reviewed by:** Prerak J. | Associate team lead, Education Management, Small-Business (50 or fewer emp.) **Reviewed Date:** December 05, 2024 **What do you like best about LobeChat?** It is a easy to use tool that helps me to connect with different AI tools like GPT, Gemini **What do you dislike about LobeChat?** Their upgrade plan's prices are a little high **What problems is LobeChat solving and how is that benefiting you?** It is helping me to search content through different AI tools like GPT and Gemini ### 15. Smart and scalable chatbots **Rating:** 4.5/5.0 stars **Reviewed by:** Prabhat a. | Customer support, Small-Business (50 or fewer emp.) **Reviewed Date:** November 26, 2024 **What do you like best about LobeChat?** Easy to use interface and makes building chatbots effortless, without any technical knowledge. **What do you dislike about LobeChat?** Pricing may be steep for small business as it has many limitations. **What problems is LobeChat solving and how is that benefiting you?** It simplifies customer interaction by providing an intuitive platform to build AI chatbots. ### 16. LobeChat **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** December 10, 2024 **What do you like best about LobeChat?** It has a user friendly interface with various customization options. It has a seamless integration between various apps **What do you dislike about LobeChat?** Certain tools are not available to integrate. Lags in support availability **What problems is LobeChat solving and how is that benefiting you?** content creation, productivity enhancement and productivity enhancement - [View LobeChat pricing details and edition comparison](https://www.g2.com/products/lobechat/reviews?section=pricing&secure%5Bexpires_at%5D=2026-07-22+02%3A37%3A57+-0500&secure%5Bsession_id%5D=41b888e4-bd90-4296-b387-1530471c9d7d&secure%5Btoken%5D=ac9872bd4bbdb972d7e8c87fdd568d8d33f0d89f479ef85d9188b89dce06205c&format=llm_user) ## LobeChat Features **Responses** - Customization - Control - Route To Human - Menu bars - Drip sequences **Platform** - Live chat - Integrations - Branding - Analytics - A/B testing - Role-based access - Collection of information **Generative AI** - AI Text Generation - AI Text Summarization ## Top LobeChat Alternatives - [Zendesk for Customer Service](https://www.g2.com/products/zendesk-for-customer-service/reviews) - 4.3/5.0 (6,652 reviews) - [Paylocity](https://www.g2.com/products/paylocity/reviews) - 4.4/5.0 (5,998 reviews) - [G2 Marketing Solutions](https://www.g2.com/products/g2/reviews) - 4.6/5.0 (5,308 reviews)