diff --git a/src/pipecat/audio/filters/aic_filter_v2.py b/src/pipecat/audio/filters/aic_filter_v2.py
deleted file mode 100644
index be2912107..000000000
--- a/src/pipecat/audio/filters/aic_filter_v2.py
+++ /dev/null
@@ -1,296 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-"""ai-coustics AIC SDK audio filter for Pipecat (aic-sdk >= 2.0.0).
-
-This module provides an audio filter implementation using ai-coustics' AIC SDK to
-enhance audio streams in real time. It mirrors the structure of other filters like
-the Koala filter and integrates with Pipecat's input transport pipeline.
-
-.. note::
-    This module is compatible with aic-sdk versions >= 2.0.0.
-    For aic-sdk < 2.0.0, use :mod:`pipecat.audio.filters.aic_filter` instead.
-"""
-
-import os
-from typing import List, Optional
-
-import numpy as np
-from loguru import logger
-
-from pipecat.audio.filters.base_audio_filter import BaseAudioFilter
-from pipecat.audio.utils import check_aic_sdk_version
-from pipecat.frames.frames import FilterControlFrame, FilterEnableFrame
-
-# Check aic-sdk is installed and version is compatible (>= 2.0.0)
-check_aic_sdk_version("v2")
-
-# AIC SDK v2 (https://ai-coustics.github.io/aic-sdk-py/api/)
-import aic
-from aic import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, VadParameter
-
-
-class AICFilter(BaseAudioFilter):
-    """Audio filter using ai-coustics' AIC SDK v2 for real-time enhancement.
-
-    Buffers incoming audio to the model's preferred block size and processes
-    planar frames in-place using float32 samples in the linear -1..+1 range.
-
-    .. note::
-        This class requires aic-sdk >= 2.0.0.
-    """
-
-    def __init__(
-        self,
-        *,
-        license_key: str = "",
-        model_id: Optional[str] = None,
-        model_path: Optional[str] = None,
-        model_download_dir: Optional[str] = None,
-        enhancement_level: Optional[float] = 1.0,
-        voice_gain: Optional[float] = 1.0,
-    ) -> None:
-        """Initialize the AIC filter.
-
-        Args:
-            license_key: ai-coustics license key for authentication.
-            model_id: Model identifier to download from CDN. Required if model_path
-                is not provided. See https://artifacts.ai-coustics.io/ for available models.
-            model_path: Optional path to a local .aicmodel file. If provided,
-                model_id is ignored and no download occurs.
-            model_download_dir: Directory for downloading models. Defaults to
-                a cache directory in user's home folder.
-            enhancement_level: Optional overall enhancement strength (0.0..1.0).
-            voice_gain: Optional linear gain applied to detected speech (0.1..4.0).
-
-        Raises:
-            ValueError: If neither model_id nor model_path is provided.
-        """
-        if model_id is None and model_path is None:
-            raise ValueError(
-                "Either 'model_id' or 'model_path' must be provided. "
-                "See https://artifacts.ai-coustics.io/ for available models."
-            )
-
-        self._license_key = license_key
-        self._model_id = model_id
-        self._model_path = model_path
-        self._model_download_dir = model_download_dir or os.path.expanduser(
-            "~/.cache/pipecat/aic-models"
-        )
-
-        self._enhancement_level = enhancement_level
-        self._voice_gain = voice_gain
-
-        self._enabled = True
-        self._sample_rate = 0
-        self._aic_ready = False
-        self._frames_per_block = 0
-        self._audio_buffer = bytearray()
-
-        # v2 API objects
-        self._model: Optional[Model] = None
-        self._processor: Optional[ProcessorAsync] = None
-        self._processor_ctx = None
-        self._vad_ctx = None
-
-    def get_vad_context(self):
-        """Return the VAD context once the processor exists.
-
-        Returns:
-            The VadContext instance bound to the underlying processor.
-            Raises RuntimeError if the processor has not been initialized.
-        """
-        if self._vad_ctx is None:
-            raise RuntimeError("AIC processor not initialized yet. Call start(sample_rate) first.")
-        return self._vad_ctx
-
-    def create_vad_analyzer(
-        self,
-        *,
-        speech_hold_duration: Optional[float] = None,
-        sensitivity: Optional[float] = None,
-    ):
-        """Return an analyzer that will lazily instantiate the AIC VAD when ready.
-
-        AIC VAD parameters (v2):
-          - speech_hold_duration:
-              How long VAD continues detecting after speech ends (in seconds).
-              Range: 0.0 .. 20x model window length, Default (SDK): 0.05s
-          - sensitivity:
-              Energy threshold sensitivity. Energy threshold = 10 ** (-sensitivity).
-              Range: 1.0 .. 15.0, Default (SDK): 6.0
-
-        Args:
-            speech_hold_duration: Optional speech hold duration to configure on the VAD.
-                If None, SDK default (0.05s) is used.
-            sensitivity: Optional sensitivity (energy threshold) to configure on the VAD.
-                Range: 1.0 .. 15.0. If None, SDK default (6.0) is used.
-
-        Returns:
-            A lazily-initialized AICVADAnalyzer that will bind to the VAD context
-            once the filter's processor has been created (after start(sample_rate)).
-        """
-        from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer
-
-        return AICVADAnalyzer(
-            vad_context_factory=lambda: self.get_vad_context(),
-            speech_hold_duration=speech_hold_duration,
-            sensitivity=sensitivity,
-        )
-
-    async def start(self, sample_rate: int):
-        """Initialize the filter with the transport's sample rate.
-
-        Args:
-            sample_rate: The sample rate of the input transport in Hz.
-
-        Returns:
-            None
-        """
-        self._sample_rate = sample_rate
-
-        try:
-            # Load or download model
-            if self._model_path:
-                logger.debug(f"Loading AIC model from: {self._model_path}")
-                self._model = Model.from_file(self._model_path)
-            else:
-                logger.debug(f"Downloading AIC model: {self._model_id}")
-                os.makedirs(self._model_download_dir, exist_ok=True)
-                model_path = await Model.download_async(self._model_id, self._model_download_dir)
-                logger.debug(f"Model downloaded to: {model_path}")
-                self._model = Model.from_file(model_path)
-
-            # Create async processor
-            self._processor = ProcessorAsync(self._model, self._license_key or "")
-
-            # Get optimal frames for this sample rate
-            self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate)
-
-            # Create configuration
-            config = ProcessorConfig(
-                sample_rate=self._sample_rate,
-                num_channels=1,
-                num_frames=self._frames_per_block,
-                allow_variable_frames=False,
-            )
-
-            # Initialize processor
-            await self._processor.initialize_async(config)
-
-            # Get contexts for parameter control and VAD
-            self._processor_ctx = self._processor.get_processor_context()
-            self._vad_ctx = self._processor.get_vad_context()
-
-            # Apply initial parameters
-            if self._enhancement_level is not None:
-                level = float(self._enhancement_level if self._enabled else 0.0)
-                self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level)
-            if self._voice_gain is not None:
-                self._processor_ctx.set_parameter(
-                    ProcessorParameter.VoiceGain, float(self._voice_gain)
-                )
-
-            self._aic_ready = True
-
-            # Log processor information
-            logger.debug(f"ai-coustics filter (v2) started:")
-            logger.debug(f"  Model ID: {self._model.get_id()}")
-            logger.debug(f"  Sample rate: {self._sample_rate} Hz")
-            logger.debug(f"  Frames per chunk: {self._frames_per_block}")
-            logger.debug(f"  Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%")
-            logger.debug(f"  Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz")
-            logger.debug(
-                f"  Output delay: {self._processor_ctx.get_output_delay()} samples "
-                f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)"
-            )
-        except Exception as e:  # noqa: BLE001 - surfacing SDK initialization errors
-            logger.error(f"AIC model initialization failed: {e}")
-            self._aic_ready = False
-
-    async def stop(self):
-        """Clean up the AIC processor when stopping.
-
-        Returns:
-            None
-        """
-        try:
-            if self._processor_ctx is not None:
-                self._processor_ctx.reset()
-        finally:
-            self._processor = None
-            self._processor_ctx = None
-            self._vad_ctx = None
-            self._model = None
-            self._aic_ready = False
-            self._audio_buffer.clear()
-
-    async def process_frame(self, frame: FilterControlFrame):
-        """Process control frames to enable/disable filtering.
-
-        Args:
-            frame: The control frame containing filter commands.
-
-        Returns:
-            None
-        """
-        if isinstance(frame, FilterEnableFrame):
-            self._enabled = frame.enable
-            if self._processor_ctx is not None:
-                try:
-                    level = float(self._enhancement_level if self._enabled else 0.0)
-                    self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level)
-                except Exception as e:  # noqa: BLE001
-                    logger.error(f"AIC set_parameter failed: {e}")
-
-    async def filter(self, audio: bytes) -> bytes:
-        """Apply AIC enhancement to audio data.
-
-        Buffers incoming audio and processes it in chunks that match the AIC
-        model's required block length. Returns enhanced audio data.
-
-        Args:
-            audio: Raw audio data as bytes to be filtered (int16 PCM, planar).
-
-        Returns:
-            Enhanced audio data as bytes (int16 PCM, planar).
-        """
-        if not self._aic_ready or self._processor is None:
-            return audio
-
-        self._audio_buffer.extend(audio)
-
-        filtered_chunks: List[bytes] = []
-
-        # Number of int16 samples currently buffered
-        available_frames = len(self._audio_buffer) // 2
-
-        while available_frames >= self._frames_per_block:
-            # Consume exactly one block worth of frames
-            samples_to_consume = self._frames_per_block * 1
-            bytes_to_consume = samples_to_consume * 2
-            block_bytes = bytes(self._audio_buffer[:bytes_to_consume])
-
-            # Convert to float32 in -1..+1 range and reshape to (channels, frames)
-            block_i16 = np.frombuffer(block_bytes, dtype=np.int16)
-            block_f32 = (block_i16.astype(np.float32) / 32768.0).reshape(
-                (1, self._frames_per_block)
-            )
-
-            # Process via async processor; returns ndarray (same shape)
-            out_f32 = await self._processor.process_async(block_f32)
-
-            # Convert back to int16 bytes
-            out_i16 = np.clip(out_f32 * 32768.0, -32768, 32767).astype(np.int16)
-            filtered_chunks.append(out_i16.reshape(-1).tobytes())
-
-            # Slide buffer
-            self._audio_buffer = self._audio_buffer[bytes_to_consume:]
-            available_frames = len(self._audio_buffer) // 2
-
-        # Do not flush incomplete frames; keep them buffered for the next call
-        return b"".join(filtered_chunks)
diff --git a/src/pipecat/audio/utils.py b/src/pipecat/audio/utils.py
index 002375f35..c61aba4dd 100644
--- a/src/pipecat/audio/utils.py
+++ b/src/pipecat/audio/utils.py
@@ -316,11 +316,41 @@ def is_silence(pcm_bytes: bytes) -> bool:
     return max_value <= SPEAKING_THRESHOLD
 
 
+def is_aic_sdk_v2() -> bool:
+    """Detect if aic-sdk v2 is installed by checking the module name.
+
+    In v2, the module was renamed from 'aic' to 'aic_sdk'.
+
+    Returns:
+        True if aic-sdk v2 (aic_sdk module) is installed, False if v1 (aic module).
+
+    Raises:
+        ImportError: If neither aic nor aic_sdk module is installed.
+    """
+    try:
+        import aic_sdk  # noqa: F401
+
+        return True
+    except ModuleNotFoundError:
+        pass
+
+    try:
+        import aic  # noqa: F401
+
+        return False
+    except ModuleNotFoundError:
+        logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.")
+        raise ImportError(
+            "aic-sdk is not installed. Install with 'pip install pipecat-ai[aic]'."
+        )
+
+
 def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None:
     """Check if the aic-sdk is installed and compatible with the module.
 
     This function checks both that the aic-sdk is installed and that its version
-    is compatible with the module requirements.
+    is compatible with the module requirements. Version detection is based on
+    the module name: v2 uses 'aic_sdk', v1 uses 'aic'.
 
     Args:
         required_version: Either "v1" (for aic-sdk < 2.0.0) or "v2" (for aic-sdk >= 2.0.0).
@@ -328,43 +358,25 @@ def check_aic_sdk_version(required_version: Literal["v1", "v2"]) -> None:
     Raises:
         ImportError: If aic-sdk is not installed or version is incompatible.
     """
-    try:
-        import aic  # noqa: F401 - check if module is installed
-    except ModuleNotFoundError as e:
-        logger.error(f"Exception: {e}")
-        logger.error("In order to use the AIC filter, you need to `pip install pipecat-ai[aic]`.")
-        raise ImportError(f"Missing module: {e}") from e
+    is_v2 = is_aic_sdk_v2()
 
-    try:
-        from importlib.metadata import version as get_version
+    if required_version == "v1" and is_v2:
+        error_msg = (
+            "aic-sdk v2 (aic_sdk module) detected, but v1 (aic module) is required. "
+            "Please use the v2 classes instead: "
+            "'from pipecat.audio.filters.aic_filter import AICFilterV2' or "
+            "'from pipecat.audio.vad.aic_vad import AICVADAnalyzerV2'."
+        )
+        logger.error(error_msg)
+        raise ImportError(error_msg)
 
-        aic_version = get_version("aic-sdk")
-        major_version = int(aic_version.split(".")[0])
-
-        if required_version == "v1" and major_version >= 2:
-            error_msg = (
-                f"aic-sdk version {aic_version} detected, but aic-sdk < 2.0.0 is required. "
-                "Please use the v2 modules instead: "
-                "'from pipecat.audio.filters.aic_filter_v2 import AICFilter' or "
-                "'from pipecat.audio.vad.aic_vad_v2 import AICVADAnalyzer'."
-            )
-            logger.error(error_msg)
-            raise ImportError(error_msg)
-
-        if required_version == "v2" and major_version < 2:
-            error_msg = (
-                f"aic-sdk version {aic_version} detected, but aic-sdk >= 2.0.0 is required. "
-                "Please update with 'pip install --upgrade aic-sdk>=2.0.0' "
-                "or use the v1 modules: "
-                "'from pipecat.audio.filters.aic_filter import AICFilter' or "
-                "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'."
-            )
-            logger.error(error_msg)
-            raise ImportError(error_msg)
-
-    except ImportError:
-        # Re-raise if it's our version mismatch error
-        raise
-    except Exception:
-        # If we can't determine version for other reasons, log warning and allow to proceed
-        logger.warning("Could not determine aic-sdk version. Proceeding anyway.")
+    if required_version == "v2" and not is_v2:
+        error_msg = (
+            "aic-sdk v1 (aic module) detected, but v2 (aic_sdk module) is required. "
+            "Please update with 'pip install --upgrade aic-sdk>=2.0.0' "
+            "or use the v1 classes: "
+            "'from pipecat.audio.filters.aic_filter import AICFilter' or "
+            "'from pipecat.audio.vad.aic_vad import AICVADAnalyzer'."
+        )
+        logger.error(error_msg)
+        raise ImportError(error_msg)
diff --git a/src/pipecat/audio/vad/aic_vad_v2.py b/src/pipecat/audio/vad/aic_vad_v2.py
deleted file mode 100644
index 2f8129a0d..000000000
--- a/src/pipecat/audio/vad/aic_vad_v2.py
+++ /dev/null
@@ -1,163 +0,0 @@
-"""AIC-integrated VAD analyzer that lazily binds to the AIC SDK v2 backend.
-
-This analyzer queries the backend's is_speech_detected() and maps it to a float
-confidence (1.0/0.0). It uses 10 ms windows based on the sample rate and applies
-optional AIC VAD parameters (speech_hold_duration, sensitivity) when available.
-
-.. note::
-    This module is compatible with aic-sdk versions >= 2.0.0.
-    For aic-sdk < 2.0.0, use :mod:`pipecat.audio.vad.aic_vad` instead.
-"""
-
-from typing import Any, Callable, Optional
-
-from loguru import logger
-
-from pipecat.audio.utils import check_aic_sdk_version
-from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADParams
-
-# Check aic-sdk is installed and version is compatible (>= 2.0.0)
-check_aic_sdk_version("v2")
-
-from aic import VadParameter
-
-
-
-class AICVADAnalyzer(VADAnalyzer):
-    """VAD analyzer that lazily binds to the AIC VadContext via a factory.
-
-    The analyzer can be constructed before the AIC Processor exists. Once the filter has
-    started and the Processor is available, the provided factory will succeed and the
-    VadContext will be obtained. We then use the context's is_speech_detected() state
-    to derive confidence values.
-
-    AIC VAD runtime parameters (v2):
-      - speech_hold_duration:
-          Controls for how long the VAD continues to detect speech after the audio signal
-          no longer contains speech (in seconds).
-          Range: 0.0 .. 20x model window length
-          Default (SDK): 0.05s (50ms)
-      - sensitivity:
-          Controls the energy threshold sensitivity. Higher values make the detector
-          less sensitive (require more energy to count as speech).
-          Range: 1.0 .. 15.0
-          Formula: Energy threshold = 10 ** (-sensitivity)
-          Default (SDK): 6.0
-
-    .. note::
-        This class requires aic-sdk >= 2.0.0.
-    """
-
-    def __init__(
-        self,
-        *,
-        vad_context_factory: Optional[Callable[[], Any]] = None,
-        speech_hold_duration: Optional[float] = None,
-        sensitivity: Optional[float] = None,
-    ):
-        """Create an AIC VAD analyzer.
-
-        Args:
-            vad_context_factory:
-                Zero-arg callable that returns the AIC VadContext.
-                This may raise until the filter's Processor has been created; the analyzer
-                will retry on set_sample_rate/first use.
-            speech_hold_duration:
-                Optional override for AIC VAD speech hold duration (in seconds).
-                Range: 0.0 .. 20x model window length.
-                If None, the SDK default (0.05s) is used.
-            sensitivity:
-                Optional override for AIC VAD sensitivity (energy threshold).
-                Range: 1.0 .. 15.0. Energy threshold = 10 ** (-sensitivity).
-                If None, the SDK default (6.0) is used.
-        """
-        # Use fixed VAD parameters for AIC: no user override
-        fixed_params = VADParams(confidence=0.5, start_secs=0.0, stop_secs=0.0, min_volume=0.0)
-        super().__init__(sample_rate=None, params=fixed_params)
-        self._vad_context_factory = vad_context_factory
-        self._vad_ctx: Optional[Any] = None
-        self._pending_speech_hold_duration: Optional[float] = speech_hold_duration
-        self._pending_sensitivity: Optional[float] = sensitivity
-
-    def bind_vad_context_factory(self, vad_context_factory: Callable[[], Any]):
-        """Attach or replace the factory post-construction."""
-        self._vad_context_factory = vad_context_factory
-        self._ensure_vad_context_initialized()
-
-    def _apply_vad_params(self):
-        """Apply optional AIC VAD parameters if available."""
-        if self._vad_ctx is None or VadParameter is None:
-            return
-        try:
-            if self._pending_speech_hold_duration is not None:
-                self._vad_ctx.set_parameter(
-                    VadParameter.SpeechHoldDuration, float(self._pending_speech_hold_duration)
-                )
-            if self._pending_sensitivity is not None:
-                self._vad_ctx.set_parameter(
-                    VadParameter.Sensitivity, float(self._pending_sensitivity)
-                )
-        except Exception as e:  # noqa: BLE001
-            logger.debug(f"AIC VAD parameter application deferred/failed: {e}")
-
-    def _ensure_vad_context_initialized(self):
-        if self._vad_ctx is not None:
-            return
-        if not self._vad_context_factory:
-            return
-        try:
-            self._vad_ctx = self._vad_context_factory()
-            self._apply_vad_params()
-            # With VAD context ready, recompute internal frame sizing
-            super().set_params(self._params)
-            logger.debug("AIC VAD context (v2) initialized in analyzer.")
-        except Exception as e:  # noqa: BLE001
-            # Filter may not be started yet; try again later
-            logger.debug(f"Deferring AIC VAD context initialization: {e}")
-
-    def set_sample_rate(self, sample_rate: int):
-        """Set the sample rate for audio processing.
-
-        Args:
-            sample_rate: Audio sample rate in Hz.
-        """
-        # Set rate and attempt VAD context initialization once we know SR
-        self._sample_rate = self._init_sample_rate or sample_rate
-        self._ensure_vad_context_initialized()
-        # Ensure params are initialized even if VAD context not ready yet
-        try:
-            super().set_params(self._params)
-        except Exception:
-            pass
-
-    def num_frames_required(self) -> int:
-        """Get the number of audio frames required for analysis.
-
-        Returns:
-            Number of frames needed for VAD processing.
-        """
-        # Use 10 ms windows based on sample rate
-        return int(self.sample_rate * 0.01) if self.sample_rate > 0 else 160
-
-    def voice_confidence(self, buffer: bytes) -> float:
-        """Calculate voice activity confidence for the given audio buffer.
-
-        Args:
-            buffer: Audio buffer to analyze.
-
-        Returns:
-            Voice confidence score is 0.0 or 1.0.
-        """
-        # Ensure VAD context exists (filter might have started since last call)
-        self._ensure_vad_context_initialized()
-        if self._vad_ctx is None:
-            return 0.0
-
-        # We do not need to analyze 'buffer' here since the processor's VAD is updated
-        # as part of the enhancement pipeline. Simply query the boolean and map it.
-        try:
-            is_speech = self._vad_ctx.is_speech_detected()
-            return 1.0 if is_speech else 0.0
-        except Exception as e:  # noqa: BLE001
-            logger.error(f"AIC VAD inference error: {e}")
-            return 0.0
diff --git a/uv.lock b/uv.lock
index 45c1f892f..4782f1c79 100644
--- a/uv.lock
+++ b/uv.lock
@@ -38,12 +38,12 @@ wheels = [
 
 [[package]]
 name = "aic-sdk"
-version = "1.2.0"
+version = "1.3.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "numpy" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f9/ba/3ebe31b91e03d42437ec864e9d2af3a52b7ccc73a1a0c1026275956270b0/aic_sdk-1.2.0.tar.gz", hash = "sha256:eeda9a181c679f175dbe6f0efc0c67ec98ff3d84cfe01541fef7fa12ecd505ca", size = 35606, upload-time = "2025-11-20T14:42:14.333Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/1f/e7/56b6074224dc26a1350b165fd0ef3c8ca8c115cc1d4aa3e4f38af9c5d3f1/aic_sdk-1.3.0.tar.gz", hash = "sha256:ccccf7c0c35fd0342a0cbcd1ed81bd3fd7f59df51fbb7c1a80fb438a94ee6ae9", size = 37700, upload-time = "2025-12-12T13:00:09.11Z" }
 
 [[package]]
 name = "aioboto3"
@@ -3292,47 +3292,47 @@ wheels = [
 
 [[package]]
 name = "mlx"
-version = "0.30.1"
+version = "0.30.3"
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