Automation Workflow Builder creates AI agent teams with access to LLM models and integrates with Zendesk, Intercom, WhatsApp, and websites. It offers features like embed options, link copying, hallucination prevention, and LLM cost optimization.Hi, nice to meet you! I'm Roy Nativ, Founder of Officely AI.
At Officely AI, we transform any process into an AI-driven operation with our innovative Team AI Builder. Unlike traditional models that rely on a single AI agent, our platform utilizes a team of specialized AI agents—each with unique personalities, objectives, and permissions, using models from GPT to Claude and LLAMA available on Hugging Face. This setup enhances problem-solving accuracy and reliability.
Our AI agents also communicate dynamically, sharing insights to deliver the most effective responses quickly. This collaborative approach is crucial for providing finely-tuned, contextually appropriate solutions.
I’m here and eager to discuss how Officely AI can transform your business operations and to answer any questions you might have about getting started!@kshitij_mishra4 thanks! Appreciate 🙏🏻Congrats on the launch 🎉! You’ve created something truly special here. I’ll definitely use it and look forward to seeing its success! 🙌🔥 @roy_nativ@zulkarnaim thanks! Appreciate 💚🙏🏻I came across this through an ad and gotta say, looks pretty cool but I’m wondering, how does the team AI thing actually work in real time, like if two agents disagree on a solution what happens then, andalso, will it make it more expensive to use multiple models instead of one, just curious about the practical side of it instead of all the big promises@codecrafteddev I’m glad you asked! A language model has many issues in a business context (for example, hallucinations, max token limitations). The right way to manage this is to split the task among several different agents. One agent based on GPT formulates search queries for RAG, another agent based on Claude crafts the response, and then another agent, based on a different model, verifies the answer and assigns a score.
Each agent has its own role. The customer feels like they’re interacting with a single agent, but behind the scenes, there’s an entire team at work. This approach also helps reduce costs by allowing the use of a cheaper model in certain cases@codecrafteddev https://youtu.be/573AFURU4EU?si=...Hey Roy, curious how your AI teams will really handle complex workflows or just another buzzword filled tech piece, what about real-world integrations, do these agents really sync seamlessly with platforms like Zendesk and Intercom or are users gonna face endless bugs and lag, hope to see some solid proof soon@contentguruny Hey Mark,
Great question! Our AI teams are built to handle complex workflows effectively, not just buzzwords. We’ve integrated seamlessly with platforms like Zendesk and Intercom.
In Zendesk, for example, we automatically scan the help center, and users can trigger our AI with an “Answer This Ticket for Me” button. The AI formulates a response, and we then track how users interact with it—whether they leave it unchanged, tweak the tone, or rewrite it completely. For cases where the response remains unchanged, we convert them into bot-driven solutions, ensuring efficiency and relevance.
Stay tuned for some solid proof—we’ve got exciting case studies already published !
Best, Roy
