Officely AI provides a low-code platform for companies to create AI processes with control and security.

Officely AI

Officely AI | 233 followers on LinkedIn. Any Process to AI
Access All LLM Models | Officely AI is an innovative solution designed to streamline and enhance support ticket resolution for organizations. Available through the Zendesk Marketplace, this platform employs a unique Team AI Builder that leverages a combination of AI agents, each equipped with distinct personalities, objectives, and tailored models including GPT, Claude, and LLaMA. This approach ensures focused control and problem-solving accuracy, significantly improving the efficiency of support services.

Founder & CEO, Officely.ai

Roy Nativ

Backend Engineer | GenAI at Officely AI

Orel Karmi

Haim Levi

Just earned a new badge: #Top5Launch ! We’re getting a lot of support, collaboration, and really special feedback about our uniqueness. Can’t wait to see what we unlock next with Product Hunt

Team of AI Agents In this example, you can see how I got Anton to play a game of 20 Questions with me. However, since Alon & Lil are part of our Guard AI team, they stepped in to ensure our interactions remain relevant to our company's solutions 💪🏿

🚀 Excited to announce Officely AI on Zendesk workspace! It starts with the "answer this ticket for me" button. Then we turn on “watch mode” to learn your behavior. After learning from your responses, our agents automatically reply to top cases where you didn't change the answer, based on your tone of voice, context, and chat history. Evaluate our team AI agents and experience the future of support! #AI #CustomerSupport #Innovation #Automation #OfficelyAI #Zendesk #SunshineAPI #GPT #Claude #Llama

There are many language models out there today. How can we tell if a new one is right for our organization in terms of capabilities, security, and price? Is a language model a structured product? A search engine? What exactly is it? Whenever there's a new release (especially from OpenAI ), I hear people saying, "Did you see the new release? Many companies will disappear now. How are you dealing with this?" First, it's important to understand that a language model is just that—a language model. It's not a search engine or a structured product for your organization (even if it has features that might suggest it is). There's a big difference between using GPT through their interface and integrating it into an organization to provide real value. There are quite a few language models, with GPT being the most well-known and easy to use. But besides GPT, there are models like Llama, Claude, Mistral, Cohere, and many others available on platforms like Hugging Face. So, if Apple releases a stronger model tomorrow (for my needs), should I replace GPT for the entire organization? It doesn't make sense. The right approach is to combine. Take the best from each, let the models interact, and use what each does best, most efficiently, authentically, and at the lowest cost. Only by combining models can we achieve the best solution. Will I have to pay for all of them? No :) When each AI agent is based on a different model, they are not all active at the same time. They only activate in scenarios that fit the type of query. At Officely AI , we create AI team agents that talk to each other, select models based on capabilities and costs, and integrate them into a single product that organizations can easily implement, control, and modify as needed with the click of a button without changing any existing methods. As new models release , our job is to allow you to add them to your AI team flow as needed, based on costs, reliability, and professional abilities.

A bit about our team builder and why we need it? Let’s start from the end - we solve support tickets for enterprise companies using AI teams, mainly through Zendesk and Intercom. There are many AI agent solutions on the Zendesk or Intercom marketplaces, you can embed LLM engines directly, and many companies allow uploading documents and asking questions. What are the existing options? You can make a direct call to LLMs, for example, GPT, and you can have one or more processes in advance before sending the question directly to the LLM engine. But does every question need to go through a long process? If I’m just asking “how are you,” why do we need a long process for that? On the other hand, there are complex issues that we would be happy if the LLM thought a little deeper before responding, like financial issues, refunds, customer retention etc. Generally, when providing sensitive information, we would prefer it to be cautious. I only gave one example of a split (and I wish it were the case in enterprise companies, but it’s far from it). Now imagine that all these tasks you have in your organization, for all departments, for all employees, are taught to a single AI agent, who is like a god that knows everything, a long prompt with many conditions and tasks. Sounds good, right? But this method has many disadvantages: • It’s very hard to maintain the rules and what to say and what not to say. • It has a capacity limit in terms of the amount of information, so you shouldn’t exaggerate (even if you use RAG). • It starts to get confused because it has many different tasks and conditions. • Limited to one model - either GPT, Claude, or any other model you want, but just one. • Lack of scalability and cost depend on a single factor. So why not treat it like we all work in our organization? I’m not supposed to do everything alone in the organization, right? Now take the scenario I described and do it with our method, of the team AI agents: Agent A - named John, his only role is to decide which of the teams he relies on to provide the best answer to the customer. That’s it, focused and short. Agent B - named Ben, his role is to search for an answer in relevant company documents. Agent C - named Eli, her role is to handle casual conversation like “how are you, what’s happening,” etc., based on general company information. And Agent D - named Gevin, his role is only to check the reliability of the response provided by Ben or Dana, our guardian. In this method, each agent has its role, its permissions, its goals, its own tone of conversation, which allows us to use different types of models in each agent; whether it’s GPT, Claude, Llama, Mistrial, and many others… Every question that is asked, all the relevant agents work together to make the answer accurate, well-founded, and correct. I’ve attached an image that illustrates everything I said.

Roy discusses the importance of preprocessing LLM models👇

Exciting developments are underway at Officely.ai for Zendesk users! Join We're introducing a cutting-edge, AI-powered customer service solution that's not just available for custom setups but will soon hit the marketplace. Here's what's on the horizon: 1. Round-the-Clock Auto-Reply with AI Agents: Imagine a team of AI agents so in tune with your brand's unique voice that every reply feels tailor-made. By analyzing past chats, our AI can mimic your team's style perfectly, ensuring consistent, authentic interactions anytime, day or night. 2. AI-Assisted Response Crafting: Our AI technology offers rapid, well-crafted draft responses directly in the text box. This enables your team to quickly review, adjust, and personalize replies, saving time without sacrificing quality or the personal touch your customers value. Furthermore, our AI agents are designed to communicate with each other and manage tasks in the background, streamlining operations and enhancing efficiency without direct human oversight. Transition to a new era of customer service with Officely.ai for Zendesk. Our smart, AI-driven support system is designed to enhance customer experiences by being quick, genuine, and always aligned with your brand's voice. Keep an eye out for our upcoming launch in the marketplace and prepare to transform your customer service with the power of AI.

Introducing the Analyst Agent 📊 Our Analyst Agent is just one of the many custom agents you can create for your business. 🔍 Benefits: 1. Streamline internal processes: From inventory management to ERP, let AI handle it seamlessly. 2. Generate insightful reports for management: Make informed decisions for your business. 3. Improve decision-making: Data-driven insights at your fingertips. 4. Enhance efficiency: Automate critical tasks for smoother operations. Imagine automating data analysis, generating real-time insights, and making data-driven decisions effortlessly. Officely's Analyst Agent does just that. Use cases: 📈 Optimize inventory levels for cost-effective operations. 📊 Manage your ERP system for greater productivity. 📉 Analyze sales data to fine-tune your strategy. 📅 Generate reports that integrate with your CRM, like Priority or any other. Join the AI revolution and integrate with ease! #AI #AnalystAgent #officelyai #dataanalytics

Exciting Opportunity with Officely's Affiliate Program 🎉 What's in it for you? *Earn a 20% commission after landing five customers, counting from number six. *Have your referrals use your unique code. It's key! 🔑 *Sweeten their deal: offer 20% off for 24 months with your code. Ready to join? Register as an affiliate online at officely.ai and start reaping the benefits today! #Officelyai #affiliates #aicommunity

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