1 Purpose
AIRQ classifies agent products along a primary taxonomy so that risk findings can be written at the class level rather than per-vendor. The taxonomy is optimized for:
- Unambiguous classification — a new agent can be placed without debate.
- Universal readability — terms work for technical, security, VC, and executive audiences.
- Attack-surface coherence — members of a class share a broadly similar AIRQ-01–AIRQ-10 profile so class-level findings are meaningful.
- Scope alignment — only end-user agent products are classified; agent infrastructure (frameworks, retrieval APIs, browser-as-a-service, vector DBs) is out of scope.
2 Design Principle
Every class is defined by its Scope — a one-line statement of what the agent does and where it acts. Sub-groups split a class along a single dimension (autonomy level, hosting model, delivery model, interaction paradigm, corpus type, or openness) where that dimension meaningfully changes product behavior or risk profile.
3 Taxonomy Overview
The ten classes, their scopes, and the number of sample agents per class.
| # | Class | Scope | Samples |
|---|---|---|---|
| 1 | General Chatbot Agents | Chat with a general-purpose AI assistant | 20 |
| 2 | Work Copilot Agents | Help one worker inside their tools | 5 |
| 3 | Coding Agents | Write and modify code | 26 |
| 4 | Browser Agents | Drive the browser | 10 |
| 5 | Computer Agents | Drive the whole computer | 13 |
| 6 | Deep Research Agents | Find and synthesize the answer | 15 |
| 7 | Internal Search Agents | Retrieve and navigate internal information | 10 |
| 8 | Real-Time Voice Agents | Operate through calls, speech, and real-time audio | 5 |
| 9 | Custom Workflow Agents | Compose tool calls into user-built flows — workflow automation | 15 |
| 10 | Business Process Agents | Run an assumed business process end-to-end — process orchestration | 49 |
| Total | 168 |
4 Class Definitions
Each class defined by a scope sentence followed by its sub-groups and sample agents.
4.1 General Chatbot Agents
Scope: Chat with a general-purpose AI assistant — standalone conversational destinations that increasingly use tools, memory, and MCPs. Distinct from Work Copilot Agents in that the chatbot is the product itself, not an assistant embedded in a work surface.
- General-purpose SaaS chatbots — ChatGPT, Claude, Google Gemini, Microsoft Copilot (consumer), Grok, Meta AI, Manus AI, Poe, DeepSeek, Mistral Le Chat, Qwen Chat
- Self-hosted chatbot frontends — LibreChat, Open WebUI, Jan, AnythingLLM, LM Studio, Msty, Chatbox AI, BionicGPT, GPT4All
4.2 Work Copilot Agents
Scope: Help one worker inside their tools — assist a single user embedded inside their daily work surface (email, documents, chat, meetings, CRM view). Acts for the individual, over that individual's data and permissions.
- Embedded copilots — Microsoft 365 Copilot, Google Gemini Workspace, Slack AI, Notion AI, Zoom AI Companion
4.3 Coding Agents
Scope: Write and modify code — operate on source code, repos, IDEs, and CLIs.
- Coding copilots (IDE-embedded, user present per suggestion) — Cursor, GitHub Copilot, Sourcegraph Cody, Continue.dev, Tabnine, Windsurf, Cline, RooCode, JetBrains Junie, Augment Code, Google Antigravity, PearAI
- Autonomous coding agents (goal → repo) — Devin, OpenAI Codex, Claude Code, Aider, SWE-Agent, Amazon Q Developer, Jules, Amp, OpenHands, Goose
- App builders (spec → deployable app) — Replit Agent, Lovable, v0 by Vercel, Bolt
4.4 Browser Agents
Scope: Drive the browser — operate web pages via navigation, forms, clicks, extraction, and page-grounded actions. Scope is one or more browser tabs.
- General-purpose browser control — OpenAI Operator, Google Project Mariner, Skyvern, Browser Use, NanoBrowser
- Chat-with-browser (agentic browsers with built-in chat) — Perplexity Comet, ChatGPT Atlas, Dia, Brave Leo, Opera Aria
4.5 Computer Agents
Scope: Drive the whole computer — operate local machine, desktop apps, filesystem, and communication surfaces. Distinguished from Browser Agents by full OS access.
- Vendor-managed computer-use — Claude Computer Use, Claude Cowork, ChatGPT Agent, Perplexity Computer
- Self-hosted computer agents — AutoGPT, OpenClaw, NemoClaw, Leon, Hermes (Nous Research), Open Interpreter, Agent S, OpenAdapt, NanoBot
4.6 Deep Research Agents
Scope: Find and synthesize the answer — ingest sources (web, papers, user-uploaded docs, structured data) and return a cited synthesis. The output is a report or dataset, not an action taken in a user system.
- Open-web research — Perplexity, OpenAI Deep Research, Gemini Deep Research, You.com Research Agent, Genspark, GPT Researcher, Open Deep Research, Local Deep Research
- Analysis & scientific research — NotebookLM, Elicit, Consensus, Scite Assistant, OpenEvidence, SciSpace, ResearchRabbit
4.7 Internal Search Agents
Scope: Retrieve and navigate internal information — closed-corpus search destinations that find and surface content inside an organisation (enterprise knowledge, legal, clinical). Distinct from Deep Research in that the output is retrieved documents and passages, not a synthesised cited report.
- Enterprise and vertical search — Glean AI, Lucidworks, Coveo, Guru, Bloomfire, Needl, Atlassian Rovo Search, Dashworks, Sana, Harvey AI
4.8 Real-Time Voice Agents
Scope: Operate through calls, speech, and real-time audio — the primary interaction channel is voice. Primary channel wins even when the underlying behaviour is support, sales, or workflow.
- Managed voice agents (vendor ships the complete agent for a specific role) — PolyAI, Parloa
- Voice agent builders (customer builds the voice agent using the platform’s SDK / studio) — Retell, Vapi, Bland
4.9 Custom Workflow Agents
Scope: Compose tool calls into user-built flows — no-code / low-code workflow automation where the customer composes a custom flow across arbitrary apps. Execution is event-triggered; state is ephemeral; the flow is authored by the customer, not shipped by the vendor.
- Closed-source — Zapier AI Agents, Make.com, Workato, Lindy AI, Gumloop, Relay.app, Tray.ai, Integrately, Retool Agents
- Open-source — n8n, Activepieces, Pipedream, Dify, Langflow, Flowise
4.10 Business Process Agents
Scope: Run an assumed business process end-to-end — vendor-shipped agents whose job is process orchestration across a multi-step domain workflow with persistent state and human handoffs. The process is given (support, sales, security investigation, ITSM, SRE); the agent fills in the details. This class spans verticals — it is a horizontal substrate class that happens to productise many vertical operations, not a vertical class in disguise.
- Process-aligned agents (vendor ships the role, customer tunes it)
- Customer support — Sierra, Ada AI, Intercom Fin, Zendesk AI Agents, Decagon, Freshworks Freddy AI Agent, DocsBot, Gorgias, Kustomer, Tidio Lyro, Front, Yuma AI, Chatwoot
- Sales & CRM — 11x, Artisan, Claygent, Salesforce Agentforce, HubSpot Breeze
- Enterprise suites — SAP Joule, Workday Illuminate
- Security & SRE — Dropzone, Prophet Security, 7AI, Simbian, Cleric, Resolve AI, PagerDuty AI, Datadog Bits, Console
- ITSM & employee support — Moveworks, ServiceNow AI Agents, Atomicwork, Aisera, Freshservice Freddy AI, Atlassian Rovo Service, BMC HelixGPT, SysAid AI Agents, ManageEngine ServiceDesk Plus AI, Rezolve.ai, Siit, eesel AI, monday service
- Agentic process builders (substrate on which customers build their own business-process agents) — Amazon Bedrock Agents, UiPath AI Agents, Microsoft Copilot Studio, Gemini Enterprise, IBM watsonx Orchestrate, Kore.ai Agent Platform, Oracle AI Agent Studio
5 Classification Rules
5.1 General Rules
One product, one class
A single product is classified into exactly one class, regardless of mode, template, or capability breadth. Classify by what the vendor canonically ships. A vendor may have multiple distinct products that land in different classes — that is normal (e.g. OpenAI ships ChatGPT, Deep Research, Operator, ChatGPT Agent, and Codex across five classes).
Cross-cutting dimensions
These dimensions apply on top of any class and can be used for secondary filtering, but do not create new classes:
- Channel — chat, voice, email, API
- Mode — copilot, autonomous, background, scheduled
- Audience — consumer, developer, enterprise-internal, enterprise-external
- Openness — closed SaaS, open-source, self-hosted, IDE plugin
- Vertical — legal, medical, sales, recruiting, finance, etc.
5.2 Class Boundaries
Several class boundaries are near-neighbors and worth explicit guidance to prevent misclassification.
General Chatbot vs Work Copilot
- General Chatbot Agents are standalone destinations (the user goes to
chatgpt.com). - Work Copilot Agents are embedded in a work surface (the copilot lives inside Outlook, Slack, Notion, etc.).
Deep Research vs General Chatbot
- General Chatbot Agents are the historical baseline — the general-purpose conversational destination. Many specialised classes (Deep Research, Browser, Computer, Coding) originated as features inside general chatbots.
- Deep Research Agents produce a distinct output (cited synthesis report, not conversational reply) with a distinct attack-surface profile (multi-source ingestion, citation integrity, longer autonomous execution). When a chatbot feature becomes a distinct use case with its own output type and risk profile — as vendors and analysts now treat deep research — it warrants separate classification.
Coding Agents vs Work Copilot
- Coding Agents operate exclusively within the code ecosystem (IDE, repo, CLI, CI/CD). The substrate is source code and developer tooling; permissions are repository-scoped.
- Work Copilot Agents operate across general-purpose business tools (email, documents, chat, calendar, CRM). The substrate is the employee’s daily work surface; permissions are identity-scoped.
Both are embedded in a work surface and assist a single user — the distinguishing axis is substrate specificity, not embedding.
Work Copilot vs Business Process
- Work Copilot Agents act for one employee inside their tools (M365 Copilot assists Alice with her email).
- Business Process Agents act for the organisation on an assumed process (Agentforce qualifies all inbound leads).
Custom Workflow vs Business Process
- Custom Workflow Agents — Workflow automation: the flow builder lets the customer compose a custom process. The vendor ships the builder; the customer authors the flow; state lives only for the execution.
- Business Process Agents — Process orchestration over an assumed process (sales outreach, support, security investigation, ITSM). The vendor ships the operator; state persists across turns; human handoffs are native.
Internal Search vs Deep Research
- Internal Search Agents retrieve and navigate inside a closed corpus; the output is documents and passages.
- Deep Research Agents synthesise a cited answer across open or user-supplied sources; the output is a structured report or dataset.
Browser vs Computer
- Browser Agents are scoped to a browser tab.
- Computer Agents have full OS access (filesystem, local apps, network).
Voice vs General Chatbot vs Business Process
- Real-Time Voice Agents — primary interaction channel is calls, speech, or real-time audio. Primary channel wins even if the underlying behaviour is support, sales, or workflow.
5.3 Out of Scope
AIRQ classifies end-user agent products. The following are agent components or code-only libraries and are explicitly out of scope:
- Retrieval APIs — Tavily, Exa, Serper, Kagi Search API
- Enterprise search infrastructure — AWS Kendra, Elastic AI Search Applications, Algolia NeuralSearch
- Browser infrastructure — Browserbase, Steel, Steel Browser, Playwright MCP, Stagehand
- Scraping / data infra — Firecrawl Agent
- Agent-builder frameworks (code-only) — LangGraph, CrewAI, AutoGen, OpenAI Assistants SDK, LlamaIndex
- Chatbot-building frameworks (code-only) — Rasa Open Source