The latest essays by columnists

Intelligence Starts Where Generic Knowledge Ends Modern chatbots have become remarkably fluent. With access to large language models (LLMs) from providers like OpenAI, organizations can deploy conversational interfaces in days, not months. These systems can answer general questions, summarize text, and simulate human-like dialogue with impressive ease. Yet, despite this apparent intelligence, many enterprise chatbots fail to deliver real operational value. They sound smart but act shallow. The core reason is simple: intelligence in a business context does not come from language fluency alone—it comes from access to proprietary business data. Without it, a chatbot remains a generic assistant rather than a reliable digital employee.

Personalizing AI Responses Based on User Role, Behavior, and Interaction History Personalization in AI-driven chatbots and assistants has evolved far beyond cosmetic UX features. Today, it is a core architectural capability that directly influences task success, trust, efficiency, and long-term adoption. Users no longer evaluate intelligent systems solely by accuracy; they assess whether the system understands who they are, how they work, and what they are trying to achieve in a given moment. In modern AI systems-especially those powered by large language models (LLMs)-effective personalization emerges from the intersection of user role, interaction behavior, and historical context. When these dimensions are modeled coherently, AI systems move from reactive responders to adaptive cognitive partners. This article examines how response personalization can be systematically designed, implemented, and governed-without falling into common traps such as overfitting, privacy erosion, or superficial “fake personalization.”

Multilingual Chatbots and Their Real-World Challenges Beyond Translation: Language, Culture, and Context in Conversational AI Multilingual chatbots have become a core component of digital interaction strategies for modern organizations—especially those operating across international, multicultural, or linguistically diverse markets. At first glance, “multilingual support” may seem like a straightforward feature: add a few languages, connect a translation engine, and deploy. In reality, multilingual conversational AI is one of the most complex and underestimated challenges in chatbot design. This article moves beyond marketing claims to examine the real, structural challenges of multilingual chatbots—the ones that directly impact user experience, system reliability, and business outcomes.

Analyzing User Conversations and Extracting Business Insights Turning Conversational Data into Strategic, Actionable Decisions In modern, data-driven organizations, user conversations have become one of the most valuable strategic assets. Every chat message, phone call, voice note, or support ticket carries signals about customer needs, expectations, frustrations, and intent. Conversation analysis powered by AI enables companies to transform this raw, unstructured dialogue into clear business insights that directly inform decision-making. Unlike traditional analytics—focused on metrics and dashboards—conversation intelligence answers deeper questions: Why are customers behaving this way? What is driving dissatisfaction or conversion? What actions should the business take next?

Sales-Oriented Chatbots vs. Support-Oriented Chatbots A Strategic, Architectural, and Business-Centric Analysis At a surface level, sales-oriented and support-oriented chatbots may appear to serve the same purpose: automated conversation with users. In practice, however, they represent two fundamentally different classes of intelligent systems. Their divergence is not limited to tone or messaging—it extends deep into goals, decision logic, data dependencies, system architecture, and business impact. For organizations designing AI-driven customer journeys, misunderstanding this distinction often leads to poor user experience, weak ROI, and misaligned expectations. This article provides a clear, non-translated, analytical breakdown tailored for decision-makers, product architects, and AI strategists.

In recent years, the rapid rise of artificial intelligence tools - from organizational chatbots to automation platforms - has significantly reshaped the digital landscape. Solutions such as CustomGPT, Chatbase, Botsonic, FastBots, Relevance AI, Dust, and even Zapier each address a specific operational need: intelligent responses, data connectivity, or workflow automation. However, a critical question arises for many organizations - particularly in the GCC region: Can these tools, on their own, function as a comprehensive enterprise management infrastructure? Based on practical and technical realities, the answer is no. This is precisely where BasisPanel AI introduces a fundamentally different approach.

A practical, system-level view of APIs, databases, and language models

How Can a Chatbot Qualify Leads Before They Reach the Sales Team? In many organizations—especially in B2B, SaaS, and professional services—the real problem is not the number of leads, but their quality. Sales teams spend a significant portion of their time engaging with prospects who lack budget, authority, urgency, or even a clear need. The result is wasted effort, long sales cycles, and declining conversion rates. This is where modern chatbots move beyond simple automation and become intelligent pre-sales systems. A well-designed chatbot can evaluate, score, and segment leads before any human interaction takes place—ensuring that sales teams only engage with qualified, high-potential prospects. This article explains how chatbots can effectively qualify leads in a structured, scalable, and business-oriented way.

Chatbots are no longer generic, one-size-fits-all tools. Real-world implementations over the past few years clearly show that a chatbot delivers real value only when its design logic, data sources, interaction model, and tone are aligned with the target industry. Differences in user behavior, regulatory constraints, decision-making processes, and interaction tempo make it impossible for a single chatbot model to perform effectively across industries. Below is a structured analysis of why each industry requires a dedicated chatbot approach—and what must be considered in its design.

In recent years, chatbots have become a core component of digital transformation across industries. One of the most common questions decision-makers ask is: Should we use a template-based chatbot or invest in a custom chatbot? The answer depends on business goals, scale, and the complexity of internal processes. This article provides a clear, practical comparison of both approaches.

Modern organizations operate in an environment shaped by data abundance, rapid change, and increasing complexity. While information is widely available, extracting meaningful insight from it has become a major challenge. Traditional research methods often fail to keep pace with the volume, diversity, and speed of today’s data landscape. This is where AI-powered deep research becomes a strategic advantage. Rather than relying on surface-level analysis or fragmented sources, deep research enables organizations to transform scattered information into structured, actionable knowledge. At Manzoomeh, deep research is viewed not as a theoretical concept, but as a practical capability that supports real business decisions.

Speech-to-Text Solutions for Modern Organizations How Manzoomeh Negaran Helps Businesses Turn Voice Data into Actionable Insight In today’s digital-first environment, organizations generate an enormous amount of spoken content every day—meetings, client calls, interviews, training sessions, and internal discussions. While this information holds significant value, much of it remains underutilized because it exists only as audio. Manzoomeh Negaran helps organizations unlock the full potential of their voice data by transforming spoken content into structured, searchable, and actionable text using advanced Speech-to-Text technologies.

BasisPanel AI is not just another management platform — it is the result of years of architectural thinking, system design, and real-world enterprise experience. Built with scalability, adaptability, and intelligence at its core, BasisPanel AI represents a new generation of organizational platforms designed for modern businesses operating in complex digital environments.

As digital products continue to evolve, the way users interact with information is changing. Text is no longer the only medium for communication. Today, voice has become a key interface—helping users consume content faster, more naturally, and with less friction.

AI Image Generation for Business Applications How Manzoomeh Negaran Enables Scalable Visual Intelligence In today’s digital landscape, visual content is no longer a complementary asset — it is a strategic component of business communication. From corporate websites and marketing campaigns to internal platforms and customer-facing systems, organizations require scalable, consistent, and intelligent image generation capabilities. Manzoomeh Negaran provides enterprise-ready AI image generation solutions that enable organizations to produce, modify, and manage visual content as part of their digital infrastructure. Built on modern AI technologies, these capabilities are designed to integrate seamlessly into real business workflows rather than operate as isolated creative tools.

In today’s digital landscape, video has emerged as one of the most effective ways to communicate, educate, engage audiences, and tell stories. From product promotions and corporate messaging to internal training and customer education, video content plays a pivotal role in business growth.

Learn how Adobe Express AI allows you to create high-quality images from simple text prompts with its cloud-based text-to-image generator. Compare it with DALL·E and Canva, see real-world applications, and hear how Firefly-powered image tools save designers time.

BasisPanel Cloud is a SaaS/PaaS-based solution that brings together a suite of back-office applications, such as CRM, ERP, project management, and finance, into a single pane of glass. Developed by Manzoomeh Negarān Group, not only does it provide integrated functionality, but it also provides the capability for custom development through its scripting language, BasisCore. BasisPanel solutions are all natively cloud-run, so there is no requirement for installing any client software on the users' computers.

Discover how Adobe Express AI can automatically remove and replace photo backgrounds using smart algorithms. Watch step by step how to create professional visuals in seconds without requiring design expertise.

Genspark AI’s Voice-Based Agent Calling enables its cloud-native Super Agent to place real phone calls using natural-sounding AI voices—automating tasks like reservations, appointment scheduling, and surveys without human intervention. Built on a multi-agent orchestration framework running entirely in the cloud, this feature parses user prompts, maps subtasks to specialized models, and synthesizes live dialogues via text-to-speech engines .Through RESTful APIs, businesses can integrate voice calling at scale—benefiting from 24/7 uptime, consistent compliance, and cost-effective outbound campaigns.

a Sparkpage is a web page created automatically by the Genspark AI system in real time. Rather than a list of links, Genspark generates a full, bespoke page on the fly based on your request. Every Sparkpage serves as an info nexus, gathering associated content from all over the web into a unified presentation. What this means in practice is that a designer or marketer may ask for a topic, say, "landing page for a fitness app," and then get a page ready with text, images, and layout elements automatically assembled. What Sparkpages distill into one resource are all those web pieces of knowledge so users never again have to dig around gathering stuff from multiple sources. Crucially, every Sparkpage features an integrated AI Copilot – a chatbot assistant embedded right on the page. This copilot allows you to pose follow-up questions or ask for edits on the page itself, so the experience is not static but dynamic. Essentially, Sparkpages provide you with an on-the-fly method for creating high-quality web content and layouts without all the standard coding.

In the evolving landscape of artificial intelligence, few platforms have made as lasting an impression as IBM Watson. Introduced in 2011 after famously winning Jeopardy!, Watson has since become a powerful suite of AI services , tailored for enterprise use, deployed on IBM Cloud, and trusted in sectors like healthcare, finance, and customer service. Let’s take a closer look at what IBM Watson offers today, its cloud-native capabilities, and why it continues to be a trusted AI solution for mission-critical applications.

As the big language models (LLMs) took off, businesses and developers called for AI solutions that are not just strong but also secure, explainable, and business-friendly. Enter Claude, the conversational AI by Anthropic, a San Francisco–headquartered AI research company that's committed to developing aligned and reliable AI solutions. In this article, we’ll explore what Claude is, how it works in the cloud, its core features, and why it’s being adopted across industries seeking ethical and scalable AI tools.

With artificial intelligence stepping into the limelight in the current era of innovation, developers and enterprises need platforms that are robust, scalable, and easy to use. Amazon SageMaker is one such solution, a product under the AWS family of technologies — giving you all that you need to create, train, and deploy machine learning models entirely in the cloud. Let's take a look at how SageMaker works, why it's so different, and why it's one of the most dependable enterprise AI development tools on the market today.

As artificial intelligence powers digital transformation, cloud AI platforms are being utilized more and more as the basis for developing scalable, secure, and fast development. One of the most accessible and powerful platforms available in this arena is Vertex AI from Google Cloud. Vertex AI is a fully managed, serverless, cloud-native machine learning platform for developing, training, deploying, and managing ML models—without the need to manage infrastructure manually. In this post, we'll discuss what makes Vertex AI unique, why its cloud-based infrastructure is groundbreaking, and how it benefits both beginners and AI teams at the enterprise level.

AI development platforms are evolving rapidly, but they all still depend on human developers to debug and test code. That is where Devin AI, a fully autonomous AI software developer created by Cognition Labs, differs. Devin is not another coding assistant like GitHub Copilot or ChatGPT. It is a smart agent that can execute complete development cycles, one of the most crucial,and sometimes longest time-consuming,being debugging and testing. In this article, we’ll explore how Devin AI automatically identifies bugs, writes test cases, runs diagnostics, and fixes problems, all without human guidance.

Learn how Devin AI transforms software development by designing, coding, testing, and deploying full projects on its own, without any human intervention. Ideal for startup founders and technical teams.

Logo AI isn't just another logo generator—it's a full branding suite that uses AI to create your whole brand identity automatically. From logo to social templates, this platform provides startups and small businesses with the professional appearance without an in-house design team.

Logo AI is an artificial intelligence-based logo creator that simplifies the entire process and makes it possible for anyone to have a finished logo in seconds. As Logo AI puts it, "Designing your own logo has never been easier! ". One enters their business name and simple preferences, and the AI generates an infinite array of possibilities instantaneously. They then choose a favorite idea and just tweak items like layouts, text, and colors in the editor. Finally, the chosen logo can be downloaded in all needed formats (high-resolution JPG, transparent PNG, PDF, and SVG/vector). Logo AI’s engine is trained on logo data and design best practices to ensure professional results. Unlike static template tools, it creates a new and unique logo for each customer. In practice, the AI applies symmetry, color theory, and typography rules to produce “beautiful” and professional designs. The site is even providing brand guidelines (colors, fonts) and various file sizes as default, just like a human designer would. The full automation has been discovered to scale: LogoAI.com says it has helped over 7 million businesses create logos (over 6.2 million logos total) through 2025. Generally, Logo AI makes it easy for non-designers to get professional-branding assets with minimal effort.

Multilingual TTS refers to the text-to-speech technology that possesses the capability of converting written text into spoken words in different languages. Modern multilingual TTS systems leverage AI-powered neural speech synthesis to generate voice output in natural voices in multiple languages. Multilingual TTS is increasingly becoming important as it eliminates the barrier of languages, allowing digital content and services to be accessed worldwide. By "expanding access to information and communication for diverse populations," multilingual TTS promotes inclusivity and leaves no one behind in our globalized world. On the practical level, multilingual TTS is able to read out content in the native language of a user, making it easier to understand for non-native speakers and those with reading or visual impairments.

ElevenLabs Voice Cloning is AI-powered text-to-speech that's able to create natural synthetic speech to imitate a voice. In practice, a user provides example recordings of a voice (e.g., 30 seconds for Instant Voice Cloning, or an hour-long for Professional Voice Cloning) and the site fine-tunes a neural model to preserve the unique pitch, timbre, and speech pattern. Once trained, the clone will have the ability to read out any text as if spoken by the original speaker. ElevenLabs' Professional Voice Cloning can reportedly generate a "near-perfect clone" of training samples and capture all the details and emotion (though it will also replicate any background noise or artefacts in the data). The website employs a voice-verification procedure (a spoken "voice-captcha") so that the owner alone can be imitated and so that each imitation is traced to the user's account so that it may not be misused. ElevenLabs supports two modes of cloning: Instant (clone of ~30 seconds of audio) and Professional (clone of 30–60+ minutes for higher fidelity). Access requires at least the Starter or Creator subscription tier. After voice samples have been uploaded, the software "fine-tunes" its own multi-lingual TTS models. In 2024 it released Eleven Multilingual v2, its flagship model, which synthesizes realistic, emotionally nuanced speech in 30+ languages. ElevenLabs reports that this model generates industry-leading emotional range and voice fidelity, with super-fast "Flash" variants (~75ms latency) for real-time use cases and a high-fidelity "Turbo" variant (~250ms latency) for subtle narration. As a whole, ElevenLabs Voice Cloning enables creators to create ultra-realistic customized voiceovers (audiobooks, dubbing, podcasts, etc.) based on user-specific training on a user's own voice, employing advanced neural networks for both expressiveness and fidelity.

Claude AI’s contextual question-answering (QA) refers to its ability to answer questions by drawing on extensive contextual information – including long documents, conversation history, or knowledge bases – rather than treating each query in isolation. It leverages a very large context window (up to 200,000 tokens or more) to “remember” and incorporate background material when formulating responses. In practice, Claude can accept entire reports, emails, or transcripts as input and provide answers to complex questions about them without being bogged down in minutiae. Anthropic has also developed specialized techniques such as prompt caching and Contextual Retrieval to further streamline this process.

Claude AI summarization and analysis capabilities are designed to work across extremely long texts. Claude 2.1 is capable of consuming up to 200,000 tokens (about 500 pages of text) per request. With such a huge context window, it is possible to upload a whole codebase, financial filings (S-1 forms), books or multi-page documents, and receive readable summaries or Q&A as output. Actually, Anthropic explains how larger context windows cut down on Claude's error rates for comprehension tasks. Anthropic benchmarks demonstrate that Claude 2.1's 200K-token window (blue bars) significantly lowers errors on long-context questions than on shorter inputs. Practically speaking, that allows Claude to summarize or compare hundreds of pages in real time – hours of work for a human. Anthropic has this in mind so that users can "streamline review of contracts, litigation preparation, and regulatory tasks, saving time and ensuring accuracy.".

Yasna AI is a research platform for conducting conversational interviews and their automatic analysis. Rather than having to read interview transcripts by hand, researchers request that Yasna's agent interview respondents (via chat or soon voice). Once interviews are conducted, Yasna automatically analyzes text data using NLP, surfacing answers to key questions, sentiment, and themes. This kind of automated qualitative analysis is crucial today because manual coding of open-ended responses is extremely time-consuming and error-prone. With automation of coding and reporting, Yasna enables teams to uncover insightful information from interviews in minutes, not weeks.

Yasna AI is a game-changing research conversation platform and automates one-to-one interviews. It has an empathic AI moderator that sends text-based conversations to real participants, mimicking the free-flowing, intuitive style of a skilled human interviewer. The researcher simply inputs their research and a guide to the system's first question, and Yasna takes the rest from there – opening chat links, posing follow-up questions, and aggregating the data. The system then translates each response transcript into efficient, structured reports. In the real world, Yasna can carry out hundreds of in-depth interviews per day, "saving you time, money and effort," says one source. The depth-speed combination makes auto interviewing with Yasna a powerful tool for acquiring qualitative insights at scale.

Gamma AI is an AI-based design platform for creating presentations, websites, and other content. The newly added feature it has released is Text-to-Visual Design, through which users can enter a text description (an idea, an outline, or a description) and get instantly a fully designed visual format—like an infographic, diagram, or timeline. In practice, a few bullet points or sentences of text are transformed into a styled page or slide with corresponding styles and graphics. Gamma's AI "crunches input context" and generates complete slides complete with text boxes, charts, and graphics. The result looks smooth and professional, even if you lack design skills. This technique lets teams skip blank slides entirely: Gamma focuses on content first, so users can spend their time thinking about what they're saying.

Gamma AI is an online design platform that creates presentations using generative AI. It's an "AI design partner" that enables users to turn ideas, outlines or existing text into well-designed slides in seconds. The main advantage of Gamma is that it gets rid of the necessity of manual design – the user just provides the content and Gamma does the layout, branding and media. As the company homepage explains, Gamma enables you to focus on your ideas by designing "beautiful slides with consistent branding" in minutes. In practice, teachers, marketers, startup founders and others use Gamma to create professional-level, interactive decks without demanding graphic design or PowerPoint skills.

NotebookLM Grounded QA is one of the most advanced features in Google’s NotebookLM platform, offering users the ability to get accurate, traceable answers based solely on the content they upload. Unlike traditional AI models that may hallucinate or provide vague answers, Grounded QA responds using only your documents — making it ideal for academic, legal, and professional use.

NotebookLM's Audio Overview is the most interesting and innovative feature provided by Google on its AI-powered notebook application. It transforms long documents into compelling, podcast-like audio experiences read in two dramatic AI voices. The feature is of greatest benefit to individuals who enjoy listening rather than reading, such as students, professionals, and creators.

NotebookLM is Google's virtual research assistant powered by artificial intelligence, intended to assist users in summarization, organization, and comprehension of their documents. It is developed based on the Gemini language model and supports integration with various formats such as Google Docs, PDFs, Slides, etc., providing an end-to-end solution for students, educators, researchers, and professionals engaged in knowledge work. Initially introduced as "Project Tailwind" in 2023, the platform has become a robust and interactive tool.

Gamma AI is a new content creation platform that employs artificial intelligence to ease creating presentations, documents, and microsites. Designed with power and simplicity, Gamma transforms plain text inputs into beautiful, visual content for sharing. Through its minimalistic UI, natural design, and live editing, Gamma becomes accessible to professionals, teachers, marketers, and artists who must focus on ideas, not formatting.

Yasna AI is an AI-powered conversational research tool that automates qualitative interviews with remarkable precision. Built to bridge the gap between traditional qualitative research and modern automation, it facilitates natural, human-like interviews at scale—without the need for live moderators. With capabilities like voice response handling, AI-based summarization, and multilingual support, Yasna is transforming the landscape of qualitative research for marketing, UX, HR, and academic fields.

Claude AI (developed by Anthropic) is one of several advanced AI chatbots on the market today. How does the free Claude.ai service compare to five other leading AI platforms – OpenAI’s ChatGPT, Google’s Gemini AI, Mistral AI, Perplexity AI, and xAI’s Grok?

Gemini is Google's latest AI interpreter for language translation and comprehension, integrated into products like Gmail, Docs, Chrome, and even voice commands. Gemini stands out from other machine translation applications because it uses Google's proprietary large language models (LLMs) to perform contextually sensitive, interactive, and multi-format translation—making it one of the most capable tools for both individuals and enterprises.

ElevenLabs AI is an advanced voice generation platform powered by artificial intelligence. It supports realistic text-to-speech, voice cloning, audio dubbing, and multilingual narration. Ideal for digital creators, educators, developers, and businesses that require natural-sounding speech at scale.

Logo AI is an intelligent, automated platform designed to help users create professional, custom logos in just minutes—no design experience required. Powered by artificial intelligence, it analyzes user inputs such as brand name, slogan, and preferred style to generate tailored logo concepts with industry-level design aesthetics.

Devin AI is an advanced artificial intelligence platform specialized in software development, known as the first fully automated software engineer. This tool is capable of independently performing complex tasks of programming, debugging, module building, testing, and project maintenance.

Explore how Genspark AI compares to top general-purpose AI agents, discover its most effective applications, the perks of its premium version, and its technical strengths in code, media, and document workflows.

Explore how Adobe Express AI stacks up against five top AI-driven design platforms, discover its ideal applications, premium benefits, and technical strengths in image, video, and document workflows.