Multimodal AI Insights

Uncover hidden business patterns by fusing text/audio/video data to empower strategic decision-making.

Applicable Scenarios

Beyond text: Unlocking visual and auditory AI productivity

Use Computer Vision (CV) to analyze production line images, automatically identifying defects and boosting QC efficiency by 300%.

Enable your knowledge base to search not just documents, but also find design blueprints and videos via 'image-to-image' search.

Automatically convert hours of meeting recordings into text with speaker diarization, generating multilingual summaries and Action Items.

Rigorous data processing and model fine-tuning pipeline

Collect proprietary image, audio, or video data, performing deduplication, annotation, and standardization.

Fine-tune open-source multimodal models (e.g., LLaVA, Whisper) or commercial APIs using your private data.

Chain speech recognition, image analysis, and LLM reasoning to build complex multi-step AI pipelines.

Quantize models for inference latency, supporting deployment on cloud GPUs or local edge computing devices.

Cutting-edge tech stack integrating perception and cognition

Visual Perception: Proficient in YOLO, Segment Anything, and Stable Diffusion models.
Voice Interaction: Integrate OpenAI Whisper and Azure Speech for high-accuracy ASR and TTS.
Multimodal LLMs: Deep integration with top models like GPT-4o and Claude 3 Opus.
Vector Search: Use Milvus/Pinecone for efficient hybrid retrieval of text and image features.

✅ Customized multimodal AI model files or APIs

✅ Model evaluation reports (Accuracy, Latency, etc.)

✅ Training datasets and data cleaning pipeline scripts

✅ Edge/Cloud deployment configuration files