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echowin provides a critical bridge between the AI agent ecosystem and the physical world of telephony. By offering a skill file for LLMs, they enable developers to give their general-purpose agents a phone to make or receive calls and access structured business knowledge. This positions them as an interaction layer in the agent stack, focusing on the PSTN (Public Switched Telephone Network) and web chat.
Their relevance to builders lies in the abstraction of complex voice latency and synthesis issues into a simple tool definition. This allows an agentic workflow—such as an autonomous recruiter—to not just screen resumes but to actually dial a candidate and conduct an initial interview using echowin's infrastructure.
Small businesses often face a binary choice in communication: answer every call personally at the cost of productivity or let them go to voicemail at the cost of revenue. echowin attempts to bridge this gap by providing an all-in-one AI agent platform that handles both voice and text-based interactions. While many competitors focus on either high-end enterprise call centers or simple website chatbots, echowin targets the small-to-medium business (SMB) segment with a no-code builder designed to turn a business's existing knowledge base into a functioning receptionist.
The core of the platform is its AI voice agent capability. Unlike traditional Interactive Voice Response (IVR) systems that rely on rigid menus, echowin uses large language models to handle natural language conversations over the phone. These agents are designed to perform specific tasks such as booking appointments, qualifying leads, and answering frequently asked questions. The platform supports over 35 voices and includes voice cloning features, allowing businesses to maintain a consistent brand persona without manual intervention.
What makes the voice implementation notable is the integration with the business's back-end. Through its Business Compass feature, the platform doesn't just record calls; it extracts intent, sentiment, and structured data from them. This turns a standard phone line into a source of business intelligence. For a local service provider like a roofing company or a law firm, this means every inquiry is automatically categorized and pushed into their CRM or project management tools via the platform's 7,000+ Zapier integrations or direct webhooks.
While the primary interface is a no-code builder, echowin has carved out a specific niche in the agent ecosystem by making its agents accessible to external LLMs. They provide a token-optimized skill file that allows users to connect their echowin agents to tools like Claude Projects, Custom GPTs, or any AI assistant that supports external knowledge. This effectively turns the echowin infrastructure—phone numbers, voice synthesis, and knowledge management—into a capability that another agent can call.
This approach reflects a broader trend in the agentic stack where communication channels are being abstracted into APIs. Instead of a developer building a custom telephony stack using Twilio and a custom orchestration layer, they can use echowin as a high-level primitive for voice interaction. The platform includes a REST API that manages contacts, agents, and calls programmatically, catering to developers who want to embed these agents into larger workflows.
The company operates on a tiered pricing model that begins with a free tier for building and testing, moving to a $49.99 per month deployment tier. Usage is billed per minute, which is standard for telephony-based AI services, though rates drop for high-volume enterprise users. The platform is remote-first and claims a user base of over 1,000 teams. By focusing on the receptionist use case, echowin avoids the complexities of full-scale contact center software while providing more utility than a simple chatbot.
No-code AI agents that handle unlimited phone calls simultaneously.
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