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AI Agent API
Other platforms stitch together STT, LLM, TTS, and telephony across multiple vendors.
SignalWire runs AI inside the media stack - the same layer handling every call.
The result is 800ms response times, zero state synchronization problems, and AI that the system controls.
Meet Sigmond. A live AI agent built on SignalWire. Ask him about our platform, AI architecture, or FreeSWITCH. He can search docs, answer questions, and even collect your info for a follow-up. This is real-time voice AI in action.
Architect AI agents directly within the media and signaling layers. No external detours. Native integration ensures sub-second round trips.
Learn MoreUse the OSS Agents SDK to run real-time Python-based voice agents. Trigger API calls mid-session, route by intent, and respond with live data. Run everything from a single Python service.
Control PSTN, SIP, WebRTC, and SMS via programmable APIs. Define how communications work without carrier lock-in or glue code.
Learn MoreRun agents locally, in containers, or serverlessly. Scale seamlessly without rewriting. Sub-800ms latency, high call quality, and built-in failover.
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Build interactive voice response systems that use speech recognition and natural language understanding instead of rigid DTMF menus. Route calls dynamically based on intent, user profile, or external API lookups, all with sub-500ms latency.
Deploy conversational AI agents that can answer questions, execute workflows, and escalate to humans when needed. Combine real-time transcription, LLM-based reasoning, and API integrations for production-grade support automation.
Create intelligent call routing that evaluates caller context, history, and external data sources to forward calls to the appropriate agent, queue, or external system. Adjust routing logic mid-call based on AI-detected intent.
Integrate AI into your contact center to handle high volumes of voice, video, and messaging interactions. Use embedded speech-to-text, translation, and LLM orchestration directly in the telecom stack for seamless agent augmentation or full automation.
Other platforms are not designed for real-time, AI-driven voice workloads. SignalWire integrates speech recognition, synthesis, and LLM orchestration directly into the media stack, avoiding the latency, context switching, and concurrency issues of external components. Instead of chaining STT, TTS, SIP signaling, IVRs, and webhooks, SignalWire provides a unified runtime for low-latency, production-grade AI agents.
Create real-time agents that manage live conversations, trigger logic mid-call, scale automatically, and integrate live data with ~800ms latency.
SignalWire's AI Agent API integrates speech recognition, LLM orchestration, and text-to-speech natively into its media and signaling layers, eliminating the fragile chains of external ASR → NLU → TTS services. Use a Python SDK or SignalWire Markup Language (SWML) to define agent logic, connect to APIs mid-call, and route to humans when needed.
SignalWire uses a Contexts and Steps system where the agent progresses through explicitly defined steps with completion criteria. At each transition, the application passes updated state into the next step's prompt via variable expansion. The AI never carries the full conversation history. Instead it receives a fresh, accurate context window at every step, preventing context drift in long interactions.
The SignalWire AI control plane is the orchestration layer that sits between the telecom infrastructure and the language model. Rather than letting the LLM drive the entire call, SignalWire keeps call state, routing logic, and telephony actions in the infrastructure layer and uses the AI as a tool within that controlled environment. This prevents the LLM from losing context and corrupting the session.
SignalWire AI agents are stateless by default. The LLM doesn't persist memory between turns. Instead, the application layer holds all call state (caller data, step progress, variables) and injects it into the prompt dynamically at each step using variable expansion. This means the AI always sees exactly what it needs, without relying on fragile LLM memory.
Yes. SignalWire AI agents can interact with callers across PSTN phone numbers, SIP endpoints, and WebRTC browser or app sessions using the same logic and workflows.
SignalWire AI agents use SWAIG (SignalWire AI Gateway) to trigger programmable "functions" during a live conversation. This allows the AI to autonomously execute actions like sending an SMS confirmation, querying a CRM database for customer records, or inserting an appointment into a calendar without human intervention or ending the call session.
Build AI voicebots that can automate higher value tasks, with far less latency and DevOps required.
