ElevenLabs Agent Workflows vs Wisry: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of ElevenLabs Agent Workflows and Wisry — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
ElevenLabs Agent Workflows
ElevenLabs
Visual graph-based editor to design sophisticated conversational agent workflows and connect them to ElevenLabs SDKs and tools.
Key features
- Visual Graph Editor: A node-based, visual interface for composing conversation flows, branching logic, and state transitions to design complex dialogues without hand-authoring code.
- SDK Integration: Native integration paths with ElevenLabs Agents SDKs (TypeScript/Swift) so visual workflows can be executed inside web, mobile, and backend applications via provided libraries and hooks.
- Tool Call Orchestration: Built-in support for invoking external tools and handling tool-call lifecycles, including programmatic approvals and responses to continue conversation flows.
- Multimodal Support: Works with audio-capable agents — manages agent audio formats and user audio, enabling voice input/output as part of workflow execution.
- Public and Private Agent Modes: Supports public agents and private agents using conversation tokens for authenticated sessions and secure deployments.
- UI Component Library Compatibility: Designed to work with ElevenLabs UI components and example apps (React, React Native, etc.) to accelerate embedding workflows into frontends.
- Session & Conversation Management: Enables starting/maintaining conversation sessions via SDK methods (e.g., useConversation/startSession) and tracks conversation IDs and context across nodes.
- Visual graph-based workflow editor for designing conversation flows
- Integration with ElevenLabs Agents SDKs (TypeScript/JavaScript and Swift)
- React integration with hooks (e.g., useConversation) to start sessions and manage conversations
- Authentication options for public and private agents, including conversation tokens
- Support for multimodal audio formats and agent audio configuration
- Tool call handling and approval workflows (MCP tool flows)
- Official UI component library to accelerate agent frontends
- Example repositories and starter packages for React, React Native (Expo), and Node
Best for
- Designing conversational IVR or voice assistant flows visually, then deploying them into mobile or web apps without hand-coding the dialogue state machine.
- Building customer-support agents that call external tools (databases, CRMs, search) from within workflow nodes and return tool results into the conversation.
- Prototyping multimodal experiences (voice + text) using ElevenLabs SDKs and UI components to iterate rapidly on dialogue structure and audio behavior.
- Embedding interactive NPC or character dialogue systems in games or simulations that require branching logic, tool integrations, and voice output.
- Creating secure private agents for internal tools by issuing conversation tokens and running workflows that access protected APIs and services.
- Integrating TTS/dubbing workflows where agent audio formats and session orchestration are managed as part of the conversation graph.
- Designing branching conversational experiences and chatbots using visual workflows
- Embedding multimodal voice agents into web and mobile apps via SDKs
- Building custom agent frontends using the ElevenLabs UI component library
- Implementing secure private-agent conversations with conversation tokens
- Handling external tool integrations and approvals within agent conversations
Wisry
Wisry
Agentic ad platform that reverse-engineers the ads already winning in your market, rebuilds them for your brand, and launches them to Meta and Google.
Key features
- Competitive ad research agents: Analyze the ads currently performing in your market and reverse-engineer the creative patterns behind them
- Evidence-backed angles: Produces a set of six messaging angles per run, each grounded in observed market performance rather than a generic template
- Brand-matched creative: Rebuilds winning concepts as static and video ads in the customer's own brand rather than reusing competitor assets
- Direct campaign launch: Pushes finished creative live to Meta and Google, optimized for return on ad spend
- End-to-end loop: Research, angles, creative and live campaign run as one continuous flow instead of separate tools and handoffs
- Trained on $1B+ ad spend: Creative and targeting models are built on a large base of historical advertising performance data
- Multi-model orchestration: Coordinates several leading foundation models rather than relying on a single provider
Best for
- An ecommerce brand entering a new category and wanting to see which creative angles already convert there before spending
- A performance marketer who needs a steady volume of fresh ad variations to fight creative fatigue
- A small DTC team without an in-house creative department producing static and video ads at agency cadence
- Testing six distinct messaging angles against each other instead of iterating on a single hypothesis
- Launching Meta and Google campaigns directly from the creative step rather than exporting assets to a separate campaign manager
- An agency scaling creative output across multiple ecommerce clients without proportional headcount