diff --git a/env.example b/env.example
index e662ea54b..6e7db21e2 100644
--- a/env.example
+++ b/env.example
@@ -156,6 +156,10 @@ PLIVO_AUTH_TOKEN=...
 # Qwen
 QWEN_API_KEY=...
 
+# Resemble AI
+RESEMBLE_API_KEY=
+RESEMBLE_VOICE_UUID=
+
 # Rime
 RIME_API_KEY=...
 RIME_VOICE_ID=...
diff --git a/examples/foundational/07zi-interruptible-resemble.py b/examples/foundational/07zi-interruptible-resemble.py
new file mode 100644
index 000000000..5cbf1288d
--- /dev/null
+++ b/examples/foundational/07zi-interruptible-resemble.py
@@ -0,0 +1,135 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import LLMRunFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import (
+    LLMContextAggregatorPair,
+    LLMUserAggregatorParams,
+)
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.services.resembleai.tts import ResembleAITTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
+from pipecat.turns.user_turn_strategies import UserTurnStrategies
+
+load_dotenv(override=True)
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+    ),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = ResembleAITTSService(
+        api_key=os.getenv("RESEMBLE_API_KEY"),
+        voice_id=os.getenv("RESEMBLE_VOICE_UUID"),
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = LLMContext(messages)
+    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
+        context,
+        user_params=LLMUserAggregatorParams(
+            user_turn_strategies=UserTurnStrategies(
+                stop=[TurnAnalyzerUserTurnStopStrategy(turn_analyzer=LocalSmartTurnAnalyzerV3())]
+            ),
+        ),
+    )
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            user_aggregator,  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            assistant_aggregator,  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMRunFrame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+    await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()
diff --git a/pyproject.toml b/pyproject.toml
index 4e879984a..0e27d597a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -100,6 +100,7 @@ piper = [ "piper-tts>=1.3.0,<2", "requests>=2.32.5,<3" ]
 playht = [ "pipecat-ai[websockets-base]" ]
 qwen = []
 remote-smart-turn = []
+resembleai = [ "pipecat-ai[websockets-base]" ]
 rime = [ "pipecat-ai[websockets-base]" ]
 riva = [ "pipecat-ai[nvidia]" ]
 runner = [ "python-dotenv>=1.0.0,<2.0.0", "uvicorn>=0.32.0,<1.0.0", "fastapi>=0.115.6,<0.128.0", "pipecat-ai-small-webrtc-prebuilt>=2.0.4"]
diff --git a/src/pipecat/services/resembleai/__init__.py b/src/pipecat/services/resembleai/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/pipecat/services/resembleai/tts.py b/src/pipecat/services/resembleai/tts.py
new file mode 100644
index 000000000..ae97982b7
--- /dev/null
+++ b/src/pipecat/services/resembleai/tts.py
@@ -0,0 +1,366 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""Resemble AI text-to-speech service implementations."""
+
+import base64
+import json
+from typing import AsyncGenerator, Optional
+
+from loguru import logger
+
+from pipecat.frames.frames import (
+    CancelFrame,
+    EndFrame,
+    ErrorFrame,
+    Frame,
+    InterruptionFrame,
+    StartFrame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+)
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.tts_service import AudioContextWordTTSService
+from pipecat.transcriptions.language import Language
+from pipecat.utils.text.base_text_aggregator import BaseTextAggregator
+from pipecat.utils.tracing.service_decorators import traced_tts
+
+try:
+    from websockets.asyncio.client import connect as websocket_connect
+    from websockets.protocol import State
+except ModuleNotFoundError as e:
+    logger.error(f"Exception: {e}")
+    logger.error("In order to use Resemble AI, you need to `pip install pipecat-ai[resembleai]`.")
+    raise Exception(f"Missing module: {e}")
+
+
+class ResembleAITTSService(AudioContextWordTTSService):
+    """Resemble AI TTS service with WebSocket streaming and word timestamps.
+
+    Provides text-to-speech using Resemble AI's streaming WebSocket API.
+    Supports word-level timestamps and audio context management for handling
+    multiple simultaneous synthesis requests with proper interruption support.
+    """
+
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        voice_id: str,
+        url: str = "wss://websocket.cluster.resemble.ai/stream",
+        precision: Optional[str] = "PCM_16",
+        output_format: Optional[str] = "wav",
+        sample_rate: Optional[int] = 22050,
+        **kwargs,
+    ):
+        """Initialize the Resemble AI TTS service.
+
+        Args:
+            api_key: Resemble AI API key for authentication.
+            voice_id: Voice UUID to use for synthesis.
+            url: WebSocket URL for Resemble AI TTS API.
+            precision: PCM bit depth (PCM_32, PCM_24, PCM_16, or MULAW).
+            output_format: Audio format (wav or mp3).
+            sample_rate: Audio sample rate (8000, 16000, 22050, 32000, or 44100). Defaults to 22050.
+            **kwargs: Additional arguments passed to the parent service.
+        """
+        super().__init__(
+            sample_rate=sample_rate,
+            **kwargs,
+        )
+
+        self._api_key = api_key
+        self._voice_id = voice_id
+        self._url = url
+        self._settings = {
+            "precision": precision,
+            "output_format": output_format,
+            "sample_rate": sample_rate,
+        }
+
+        self._websocket = None
+        self._request_id_counter = 0
+        self._current_request_id = None
+        self._receive_task = None
+
+        self.set_voice(voice_id)
+
+    def can_generate_metrics(self) -> bool:
+        """Check if this service can generate processing metrics.
+
+        Returns:
+            True, as Resemble AI service supports metrics generation.
+        """
+        return True
+
+    def _build_msg(self, text: str = "") -> str:
+        """Build a JSON message for the Resemble AI WebSocket API.
+
+        Args:
+            text: The text or SSML to synthesize.
+
+        Returns:
+            JSON string containing the request payload.
+        """
+        msg = {
+            "voice_uuid": self._voice_id,
+            "data": text,
+            "binary_response": False,  # Use JSON frames to get timestamps
+            "request_id": self._request_id_counter,
+            "output_format": self._settings["output_format"],
+            "sample_rate": self._settings["sample_rate"],
+            "precision": self._settings["precision"],
+            "no_audio_header": True,
+        }
+
+        self._request_id_counter += 1
+        return json.dumps(msg)
+
+    async def start(self, frame: StartFrame):
+        """Start the Resemble AI TTS service.
+
+        Args:
+            frame: The start frame containing initialization parameters.
+        """
+        await super().start(frame)
+        self._settings["sample_rate"] = self.sample_rate
+        await self._connect()
+
+    async def stop(self, frame: EndFrame):
+        """Stop the Resemble AI TTS service.
+
+        Args:
+            frame: The end frame.
+        """
+        await super().stop(frame)
+        await self._disconnect()
+
+    async def cancel(self, frame: CancelFrame):
+        """Cancel the Resemble AI TTS service.
+
+        Args:
+            frame: The cancel frame.
+        """
+        await super().cancel(frame)
+        await self._disconnect()
+
+    async def _connect(self):
+        """Connect to the Resemble AI WebSocket."""
+        await self._connect_websocket()
+
+        if self._websocket and not self._receive_task:
+            self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
+
+    async def _disconnect(self):
+        """Disconnect from the Resemble AI WebSocket."""
+        if self._receive_task:
+            await self.cancel_task(self._receive_task)
+            self._receive_task = None
+
+        await self._disconnect_websocket()
+
+    async def _connect_websocket(self):
+        """Establish WebSocket connection to Resemble AI."""
+        try:
+            if self._websocket and self._websocket.state is State.OPEN:
+                return
+            logger.debug("Connecting to Resemble AI TTS")
+            headers = {"Authorization": f"Bearer {self._api_key}"}
+            self._websocket = await websocket_connect(self._url, additional_headers=headers)
+            await self._call_event_handler("on_connected")
+        except Exception as e:
+            logger.error(f"{self} exception: {e}")
+            await self.push_error(ErrorFrame(error=f"{self} error: {e}"))
+            self._websocket = None
+            await self._call_event_handler("on_connection_error", f"{e}")
+
+    async def _disconnect_websocket(self):
+        """Close WebSocket connection to Resemble AI."""
+        try:
+            await self.stop_all_metrics()
+
+            if self._websocket:
+                logger.debug("Disconnecting from Resemble AI")
+                await self._websocket.close()
+        except Exception as e:
+            logger.error(f"{self} exception: {e}")
+            await self.push_error(ErrorFrame(error=f"{self} error: {e}"))
+        finally:
+            self._current_request_id = None
+            self._websocket = None
+            await self._call_event_handler("on_disconnected")
+
+    def _get_websocket(self):
+        """Get the current WebSocket connection.
+
+        Returns:
+            The active WebSocket connection.
+
+        Raises:
+            Exception: If websocket is not connected.
+        """
+        if self._websocket:
+            return self._websocket
+        raise Exception("Websocket not connected")
+
+    async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection):
+        """Handle interruption by stopping current synthesis.
+
+        Args:
+            frame: The interruption frame.
+            direction: The direction of frame processing.
+        """
+        await super()._handle_interruption(frame, direction)
+        await self.stop_all_metrics()
+        # Note: Resemble AI doesn't have an explicit cancel mechanism,
+        # but we can stop processing by resetting our current request_id
+        self._current_request_id = None
+
+    async def flush_audio(self):
+        """Flush any pending audio and finalize the current context."""
+        if not self._current_request_id:
+            return
+        logger.trace(f"{self}: flushing audio")
+        # For Resemble AI, we just wait for the audio_end message
+        # which is handled in _process_messages
+        self._current_request_id = None
+
+    async def _process_messages(self):
+        """Process incoming WebSocket messages from Resemble AI."""
+        async for message in self._get_websocket():
+            try:
+                msg = json.loads(message)
+            except json.JSONDecodeError:
+                logger.error(f"{self} received invalid JSON: {message}")
+                continue
+
+            if not msg:
+                continue
+
+            msg_type = msg.get("type")
+            request_id = msg.get("request_id")
+
+            # Convert request_id to string for audio context tracking
+            request_id_str = str(request_id)
+
+            # Check if this message belongs to a valid audio context
+            if not self.audio_context_available(request_id_str):
+                continue
+
+            if msg_type == "audio":
+                await self.stop_ttfb_metrics()
+                await self.start_word_timestamps()
+
+                # Decode base64 audio content
+                audio_content = msg.get("audio_content", "")
+                if audio_content:
+                    audio_data = base64.b64decode(audio_content)
+                    frame = TTSAudioRawFrame(
+                        audio=audio_data,
+                        sample_rate=self.sample_rate,
+                        num_channels=1,
+                    )
+                    await self.append_to_audio_context(request_id_str, frame)
+
+                # Process timestamps if available
+                timestamps = msg.get("audio_timestamps", {})
+                if timestamps:
+                    graph_chars = timestamps.get("graph_chars", [])
+                    graph_times = timestamps.get("graph_times", [])
+
+                    # Convert graph_times (start, end pairs) to word timestamps
+                    word_times = []
+                    for char, times in zip(graph_chars, graph_times):
+                        if times and len(times) >= 2:
+                            start_time = times[0]
+                            word_times.append((char, start_time))
+
+                    if word_times:
+                        await self.add_word_timestamps(word_times)
+
+            elif msg_type == "audio_end":
+                await self.stop_ttfb_metrics()
+                await self.add_word_timestamps([("TTSStoppedFrame", 0), ("Reset", 0)])
+                await self.remove_audio_context(request_id_str)
+                # Clear current request if this was it
+                if self._current_request_id == request_id:
+                    self._current_request_id = None
+
+            elif msg_type == "error":
+                error_name = msg.get("error_name", "Unknown")
+                error_msg = msg.get("message", "Unknown error")
+                status_code = msg.get("status_code", 0)
+                logger.error(f"{self} error: {error_name} (status {status_code}): {error_msg}")
+                await self.push_frame(TTSStoppedFrame())
+                await self.stop_all_metrics()
+                await self.push_error(ErrorFrame(error=f"{self} error: {error_name} - {error_msg}"))
+
+                # Clear current request if this was it
+                if self._current_request_id == request_id:
+                    self._current_request_id = None
+
+                # Check if this is an unrecoverable error (connection-level failure)
+                if status_code in [401, 403]:
+                    # Close and reconnect for auth errors
+                    await self._disconnect_websocket()
+                    await self._connect_websocket()
+            else:
+                logger.warning(f"{self} unknown message type: {msg_type}")
+
+    async def _receive_messages(self):
+        """Main loop for receiving messages from Resemble AI."""
+        while True:
+            try:
+                await self._process_messages()
+            except Exception as e:
+                logger.error(f"{self} error in receive loop: {e}")
+                # Try to reconnect
+                logger.debug(f"{self} Resemble AI connection lost, reconnecting")
+                await self._connect_websocket()
+
+    @traced_tts
+    async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
+        """Generate speech from text using Resemble AI's streaming API.
+
+        Args:
+            text: The text to synthesize into speech.
+
+        Yields:
+            Frame: Audio frames containing the synthesized speech.
+        """
+        logger.debug(f"{self}: Generating TTS [{text}]")
+
+        try:
+            if not self._websocket or self._websocket.state is State.CLOSED:
+                await self._connect()
+
+            if not self._current_request_id:
+                await self.start_ttfb_metrics()
+                yield TTSStartedFrame()
+                # Track the current request_id we're processing
+                self._current_request_id = self._request_id_counter
+
+            # Create audio context using request_id (converted to string)
+            request_id_str = str(self._request_id_counter)
+            await self.create_audio_context(request_id_str)
+
+            msg = self._build_msg(text=text)
+
+            try:
+                await self._get_websocket().send(msg)
+                await self.start_tts_usage_metrics(text)
+            except Exception as e:
+                logger.error(f"{self} exception: {e}")
+                yield ErrorFrame(error=f"{self} error: {e}")
+                yield TTSStoppedFrame()
+                await self._disconnect()
+                await self._connect()
+                return
+            yield None
+        except Exception as e:
+            logger.error(f"{self} exception: {e}")
+            yield ErrorFrame(error=f"{self} error: {e}")
diff --git a/uv.lock b/uv.lock
index 6fd35f166..96e901299 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2110,6 +2110,7 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fe/65/5b235b40581ad75ab97dcd8b4218022ae8e3ab77c13c919f1a1dfe9171fd/greenlet-3.3.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:04bee4775f40ecefcdaa9d115ab44736cd4b9c5fba733575bfe9379419582e13", size = 273723, upload-time = "2026-01-23T15:30:37.521Z" },
     { url = "https://files.pythonhosted.org/packages/ce/ad/eb4729b85cba2d29499e0a04ca6fbdd8f540afd7be142fd571eea43d712f/greenlet-3.3.1-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:50e1457f4fed12a50e427988a07f0f9df53cf0ee8da23fab16e6732c2ec909d4", size = 574874, upload-time = "2026-01-23T16:00:54.551Z" },
     { url = "https://files.pythonhosted.org/packages/87/32/57cad7fe4c8b82fdaa098c89498ef85ad92dfbb09d5eb713adedfc2ae1f5/greenlet-3.3.1-cp310-cp310-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:070472cd156f0656f86f92e954591644e158fd65aa415ffbe2d44ca77656a8f5", size = 586309, upload-time = "2026-01-23T16:05:25.18Z" },
+    { url = "https://files.pythonhosted.org/packages/66/66/f041005cb87055e62b0d68680e88ec1a57f4688523d5e2fb305841bc8307/greenlet-3.3.1-cp310-cp310-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:1108b61b06b5224656121c3c8ee8876161c491cbe74e5c519e0634c837cf93d5", size = 597461, upload-time = "2026-01-23T16:15:51.943Z" },
     { url = "https://files.pythonhosted.org/packages/87/eb/8a1ec2da4d55824f160594a75a9d8354a5fe0a300fb1c48e7944265217e1/greenlet-3.3.1-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3a300354f27dd86bae5fbf7002e6dd2b3255cd372e9242c933faf5e859b703fe", size = 586985, upload-time = "2026-01-23T15:32:47.968Z" },
     { url = "https://files.pythonhosted.org/packages/15/1c/0621dd4321dd8c351372ee8f9308136acb628600658a49be1b7504208738/greenlet-3.3.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:e84b51cbebf9ae573b5fbd15df88887815e3253fc000a7d0ff95170e8f7e9729", size = 1547271, upload-time = "2026-01-23T16:04:18.977Z" },
     { url = "https://files.pythonhosted.org/packages/9d/53/24047f8924c83bea7a59c8678d9571209c6bfe5f4c17c94a78c06024e9f2/greenlet-3.3.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:e0093bd1a06d899892427217f0ff2a3c8f306182b8c754336d32e2d587c131b4", size = 1613427, upload-time = "2026-01-23T15:33:44.428Z" },
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@@ -4551,6 +4557,9 @@ piper = [
 playht = [
     { name = "websockets" },
 ]
+resembleai = [
+    { name = "websockets" },
+]
 rime = [
     { name = "websockets" },
 ]
@@ -4718,6 +4727,7 @@ requires-dist = [
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     { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'openai'" },
     { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'playht'" },
+    { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'resembleai'" },
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     { name = "pipecat-ai", extras = ["websockets-base"], marker = "extra == 'sarvam'" },
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@@ -4757,7 +4767,7 @@ requires-dist = [
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+provides-extras = ["aic", "anthropic", "assemblyai", "asyncai", "aws", "aws-nova-sonic", "azure", "cartesia", "camb", "cerebras", "daily", "deepgram", "deepseek", "elevenlabs", "fal", "fireworks", "fish", "gladia", "google", "gradium", "grok", "groq", "gstreamer", "heygen", "hume", "inworld", "koala", "kokoro", "krisp", "langchain", "livekit", "lmnt", "local", "local-smart-turn", "local-smart-turn-v3", "mcp", "mem0", "mistral", "mlx-whisper", "moondream", "neuphonic", "noisereduce", "nvidia", "openai", "rnnoise", "openpipe", "openrouter", "perplexity", "piper", "playht", "qwen", "remote-smart-turn", "resembleai", "rime", "riva", "runner", "sagemaker", "sambanova", "sarvam", "sentry", "silero", "simli", "soniox", "soundfile", "speechmatics", "strands", "tavus", "together", "tracing", "ultravox", "webrtc", "websocket", "websockets-base", "whisper"]
 
 [package.metadata.requires-dev]
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