Our Qinch Technology

Qinch.ai excels at transforming enterprise data into structured, actionable insights through our advanced AI techniques. Our technology leverages machine learning, natural language processing (NLP), computer vision, and large language models (LLMs) to analyze data, understand context, and generate intelligent solutions.

Qinch's Technological Edge

Qinch Knowledge Processor (QKP)
- Demonstrated improvements in retrieval accuracy, contextual relevance, and information correctness.
- A novel architecture combining AI agents, multiple LLMs, vector representations, and graph databases.
- Integration of AI web search for knowledge expansion and correctness.
- An effective method for topic isolation within knowledge retrieval systems.

Qinch Intelligence Engine (QIE)

diagram of qinch knowledge processor

Organizing Enterprise Data

Enterprise data comprises both structured and unstructured formats, presenting a challenge for organizations aiming to derive valuable insights. Qinch AI provides a robust methodology to effectively organize and enable the extraction of actionable insights.

Qinch AI Agents for Accuracy and Reliability

Our innovative approach breaks down complex AI tasks into smaller, specialised sub-tasks. Each is handled by dedicated AI agents, ensuring high precision and reliability. These multi-modal AI agents are self-reflective and corrective, incorporating deterministic features to consistently deliver accurate results.

Purposeful AI-Driven Applications

With vast amounts of enterprise data generated continuously, it is highly critical for efficient data funnelling and learning to fully leverage its rich potential. Leveraging on Qinch’s technology, organizations can reap the benefits of AI-driven applications that drive informed decision-making and operational efficiency.‍

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Recent articles

MAS commits S$100 million to support quantum, AI capabilities in financial sector

What’s the future of AI?

Data Suggests Growth in Enterprise Adoption of AI is Due to Widespread Deployment by Early...

10 january 2024

The who, what, and where of AI adoption in America

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Enterprise Governance, Risk, and Compliance (eGRC) Market Size, Share & Industry Analysis, By Component (Software and Services), By Deployment Model (Cloud-based, On-premise), By Organization Size (Large Enterprises, and Small and Medium Enterprises (SMEs)), By Vertical (BFSI, Healthcare, Government, Energy & Utilities, Manufacturing, Retail & Consumer Goods, Telecom & IT, and Others), and Regional Forecast, 2024-2032

MAS commits S$100 million to support quantum, AI capabilities in financial sector

What’s the future of AI?

Data Suggests Growth in Enterprise Adoption of AI is Due to Widespread Deployment by Early...

10 january 2024

The who, what, and where of AI adoption in America

7 february 2024

Enterprise Governance, Risk, and Compliance (eGRC) Market Size, Share & Industry Analysis, By Component (Software and Services), By Deployment Model (Cloud-based, On-premise), By Organization Size (Large Enterprises, and Small and Medium Enterprises (SMEs)), By Vertical (BFSI, Healthcare, Government, Energy & Utilities, Manufacturing, Retail & Consumer Goods, Telecom & IT, and Others), and Regional Forecast, 2024-2032