Company patents
GONG.io Ltd.
GONG.io Ltd. surprisingly shows a strong, albeit recent, focus on core AI technologies, with Speech Processing (42.9% of portfolio), Databases & Information Retrieval (28.6%), and Natural Language Processing (26.5%) dominating its patent portfolio, all experiencing significant growth in 2024 (e.g., Speech Processing at +400.0% YoY). However, the company appears to be shifting priorities away from several categories, with Machine Learning & AI, Messaging & Email, Routing, Switching & QoS, Pictorial / Video Communications, and Input/Output & User Interfaces all showing a 100.0% decline in patent filings in 2025, and a general slowdown across most categories so far in 2026.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
49 US filings (since 2023) · 12 categories · 13 themes
Techniques for enhancing, encoding, decoding, or separating speech and audio signals, often involving multi-microphone arrays, acoustic echo cancellation, beamforming, or advanced audio compression for improved clarity and quality.
Techniques for generating human-like text or other content using large pre-trained models, often involving prompt engineering, speculative decoding, or multi-modal inputs for content creation.
Techniques for improving the perceived quality, synchronization, and moderation of audio and voice streams, often involving codec management, transcoding, and content analysis.
Methods and systems for identifying, extracting, and structuring specific entities, relationships, or insights from text-based documents, often involving techniques like named entity recognition, relation extraction, or summarization.
Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.
Technologies for generating artificial speech that is personalized, context-aware, or adaptable to specific virtual agents or messaging campaigns, often utilizing text-to-speech (TTS) and audio caching for efficient delivery.
Methods and systems for integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.
Techniques for distributing computational tasks, data storage, and service logic across cloud data centers, edge devices, and user equipment to improve performance, resilience, or resource utilization. This includes architectures for split rendering, decentralized ledgers, and microservices.
Techniques to improve the accuracy and robustness of Automatic Speech Recognition (ASR) systems by incorporating contextual information, dynamic hint words, or customized machine learning models for specific domains or users.
AI systems designed to engage in natural language dialogue, maintain conversation state, understand user intent, and generate relevant responses, often across multiple communication channels or modalities.
Methods and systems for identifying synthetic or manipulated speech (deepfake audio) using forensic analysis of audio features, such as breath patterns, vocoder signatures, or machine learning models to determine authenticity.
Applications of speech processing and artificial intelligence for medical diagnosis, therapeutic interventions, or accessibility solutions, particularly for conditions affecting speech production or hearing.
Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.
Patents
Showing 1-6 of 6
Distributed Cloud/Edge Processing