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111 Listings in AI Assistants Available
What is ChatGPT? ChatGPT is OpenAI's conversational AI assistant, used for writing, analysis, coding, research and image generation. It is offered as a free tier plus paid individual, business and enterprise plans. Key capabilities of ChatGPT Conversational assistant: answers questions and drafts text Writing and editing: emails, documents and summaries Coding help: writes and explains code Data analysis: works on uploaded files Image generation: available with limits on free tier Deep research: multi-step web research How ChatGPT works You type a prompt, upload a file or speak, and ChatGPT replies using OpenAI's models. Higher plans raise message limits and unlock more capable models and tools. The free tier gives limited access to models, messages and image generation. Who uses ChatGPT? Individuals, students, developers and organizations use it. Business suits teams with admin controls, and Enterprise, generally aimed at organizations of around 150 or more users, is custom priced. ChatGPT pricing The vendor pricing page returned a 403, so these figures come from third-party coverage. Free is $0, Go is $8 a month, Plus is $20, Business is $25 per user monthly ($20 annual), and Pro tiers start at $100 or $200. Enterprise is custom. ChatGPT alternatives Alternatives include Meta AI inside Meta apps, Poe for multiple bots in one app, Le Chat from Mistral, Grok from xAI, and Character.AI for persona chat.
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What is H Company? H Company is a frontier AI research lab and agentic platform that builds computer-use agents. Its Holo multimodal models power agents that operate desktops and browsers, and the vendor describes the offering as operational intelligence for the enterprise. Key capabilities of H Company Holo models: Multimodal models for computer use; Holo4 comes in 27B and 35B-A3B variants. Agents API: Cloud-hosted agents for desktop and browser automation. Models API: OpenAI-compatible access to Holo models. HoloTab: Free Chrome extension to try computer-use agents without signup. Enterprise deployment: On-site Forward Deployed Engineers build custom agents. Works with existing software: No integrations or rebuilds required. How H Company works Agents see and act on screens like a person, so they work across existing software without custom integrations. Developers call the Agents API for hosted sessions, or call Holo models directly through an OpenAI-compatible Models API. Holo4 scores 85.2% (27B) and 80.8% (35B-A3B) on the OSWorld benchmark, per the vendor. Who uses H Company? Developers building automation, builders trying the free tier, and European enterprises that want custom agents. HoloTab lets individuals try computer-use agents in Chrome without signing up. H Company pricing Agents API plans: Free at $0 with about 60 sessions per month, Builder at $20 per month with about 1,000 sessions, Startup at $200 per month with about 10,000 sessions, and custom Enterprise. H Company alternatives Related tools include Ema, Skywork, Manus, Magical and Limitless, which cover general agents and task automation.
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See where ai assistants fits in a complete stack, with the other software, AI agents and services each business needs.
What is Samsung Food? Samsung Food is a meal planning AI agent offering a food platform from Samsung that uses AI to personalize recipes, meal plans and shopping lists. Samsung Food helps home cooks and families automate meal planning work and get results faster. Key capabilities of Samsung Food Recipe saving AI meal planning Nutrition info Smart appliance guided cooking Personalized meal plans Smart appliance cooking How Samsung Food works Samsung Food takes text and images as input and produces recipes and meal plans. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Samsung SmartThings, Instacart, Amazon Fresh and iOS, so the agent works inside existing workflows. Who uses Samsung Food? Samsung Food is built for home cooks and families. It suits teams that want recipe saving and AI meal planning without adding headcount, while keeping people in control of review and final decisions. Samsung Food vs Mealime Samsung Food is often compared with Mealime. Samsung Food stands out for recipe saving and nutrition info. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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AI assistants are general-purpose, LLM-powered helpers that answer questions, draft content, automate tasks, and work across your tools and knowledge, for individuals and teams. This guide explains what AI assistants are, how they work, what matters, and how to choose one.
AI assistants are general-purpose, LLM-powered helpers that answer questions, draft content, automate tasks, and work across your tools and knowledge, for individuals and teams. This guide explains what AI assistants are, how they work, what matters, and how to choose one.
An AI assistant is a conversational, LLM-powered tool that helps with a broad range of work: answering questions, writing and summarizing, analyzing documents, and increasingly taking actions across connected apps and data.
Unlike narrow single-task bots, assistants are general-purpose and extensible, grounded in your knowledge, connected to tools via integrations, and often customizable with custom instructions, skills, or agents.
The category spans consumer and enterprise assistants, embedded copilots inside productivity suites, and platforms for building custom assistants over company knowledge. Buyers weigh capability and accuracy, knowledge grounding, data security, and integration with their stack.
A user asks a question or gives a task in natural language; the assistant uses an LLM, optionally grounded in your documents and connected apps, to respond, generate content, or take actions, maintaining context across the conversation.
Platforms combine one or more LLMs, retrieval grounding over your knowledge, tool/app integrations, and controls for permissions and safety, often with customization via instructions, custom assistants, or workflows.
Individuals and teams connect knowledge sources and apps, configure custom assistants and permissions, and use the assistant for daily work, with admins governing access, data, and usage.
Answer questions, draft and edit content, summarize, and brainstorm across any topic or task.
Ground responses in your documents and data so answers are accurate and company-specific.
Connect to your apps to retrieve information and take actions, not just chat.
Create tailored assistants with custom instructions, knowledge, and capabilities for specific roles.
Work with text, documents, images, and increasingly voice and data files.
Permissions, data controls, and audit for safe team and enterprise deployment.
A single assistant accelerates writing, research, analysis, and everyday knowledge work.
Grounded assistants answer from company knowledge so people find information fast.
Connected assistants take actions across apps, reducing manual steps.
Custom assistants tailor capabilities to teams and workflows.
Bring answers and actions into one interface instead of juggling apps.
| Type | Best for | Ideal size | Pros | Limitations |
|---|---|---|---|---|
| General-purpose assistants | Broad Q&A, writing, analysis | Any | Versatile, easy to adopt | Generic without grounding |
| Enterprise knowledge assistants | Answers grounded in company data | Mid-market to enterprise | Accurate, secure, governed | Setup and data connection |
| Embedded copilots | AI inside productivity/SaaS suites | Any | In-context, no switching | Tied to one ecosystem |
| Custom assistant platforms | Build tailored assistants/agents | SMB to enterprise | Fit to specific workflows | Requires configuration |
Technology: Technology teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Healthcare: Healthcare teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Financial Services: Financial Services teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Retail & E-commerce: Retail & E-commerce teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Education: Education teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Professional Services: Professional Services teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Manufacturing: Manufacturing teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Media: Media teams use AI assistants to answer questions from company knowledge, draft and analyze content, and automate tasks across their tools, with governance over data and access.
Test on your real tasks and questions; evaluate response quality, reasoning, and grounding accuracy.
Confirm it can connect to and accurately answer from your documents and data.
Check connections to your apps and whether the assistant can take actions, not just chat.
Verify data controls, permissions, no-training guarantees, and admin/audit features.
Assess custom assistants, instructions, and workflow building for your roles.
Understand per-seat or usage pricing and how it scales across the team.
Assistants are evolving into agents that complete multi-step tasks across apps with oversight.
Deeper, secure grounding in company knowledge is making answers accurate and trustworthy.
Multimodal and voice interfaces are broadening how people work with assistants.
Buyers should prioritize capability and grounding accuracy, integrations and actions, strong security and governance, and customization.
An AI assistant is a general-purpose, LLM-powered tool that helps with a broad range of work, answering questions, writing and summarizing, analyzing documents, and increasingly taking actions across connected apps. Unlike narrow task bots, assistants are extensible and can be grounded in your knowledge and customized with instructions and skills, available as consumer tools, enterprise assistants, embedded copilots, and custom-build platforms.
Chatbots are typically built for a specific purpose like customer support and a defined audience. AI assistants are general-purpose helpers for a wide range of tasks, often for internal users, with broader capabilities, knowledge grounding, app integrations, and customization. The line is blurring as both grow more capable, but assistants emphasize versatility and action across tools.
Enterprise assistants can connect to and ground answers in your documents, wikis, and data so responses are accurate and company-specific rather than generic. This requires secure integration and proper permissions, confirm how the assistant retrieves, secures, and controls access to your knowledge before connecting sensitive data.
Reputable enterprise assistants offer encryption, SSO, role-based permissions, audit logs, and no-training guarantees on business data. Security varies widely, especially between consumer and enterprise tiers, so confirm data handling, residency, and governance controls before deploying across a team.
Increasingly, yes. Through app integrations, assistants can retrieve information and perform actions, creating records, sending messages, updating systems, and agentic assistants can complete multi-step tasks. The depth of integration determines what's possible, so verify the specific actions and apps you need are supported.
Assistants are built on large language models, and some platforms let you choose among models or use the latest frontier models. Model choice affects capability, speed, and cost. If model flexibility matters, confirm which models are available and whether you can select or switch them.
Common models are per-seat subscriptions, usage-based (tokens or messages), or as features within productivity suites, often with tiers for advanced models, knowledge grounding, and admin controls. Estimate your team size and usage, and weigh grounding and governance features alongside cost.
Prioritize capability and accuracy on your real tasks, knowledge grounding, integrations and the ability to take actions, security and governance, customization, and pricing. Decide whether you need a general assistant, an enterprise knowledge assistant, or a custom-build platform, and trial it on real workflows before rolling out.
