Paige
Paige is a tool developed by Cognaize that utilizes AI to rapidly collect documents specific to the financial industry from the internet.
It streamlines the process of obtaining the latest, most relevant reports by automating the search and retrieval tasks.
Unstructured Data
Information in various formats including text-heavy documents such as emails, articles, PDFs, Excel, Word documents, PowerPoints, HTML pages, chat protocols, as well as documents heavy on numbers and tables.
Examples are loan agreements, ESG reports or SEC filings.
Expert Knowledge
Highly specialized information and insights contributed by financial experts.
This knowledge is used to guide model training, ensuring the AI's outputs are accurate and reflect expert-level understanding.
Corpus of Knowledge
A collection of rules, definitions and other documents that AI uses to learn and refine its understanding of specific use cases or document types to produce the desired output.
Customers can upload their own ontologies or use the Cognaize corpus of knowledge developed over four years of AI-based document automation. An example is the definition of COGS that could vary significantly across different financial services firms.
Cognaize Foundation Models
AI models developed by Cognaize that provide the basic architecture for various AI applications.
They are built from the ground up to support advanced document analysis tasks such as section prediction and table recognition.
Closed Domain Models
AI models designed to operate within a narrowly defined area with high expertise and accuracy.
These models are optimized to handle specific types of queries or data in particular fields.
Precise Language Models
Specialized AI models fine-tuned and downsized for the financial domain.
They undergo rigorous training to grasp the nuances and jargon of the financial sector, resulting in high accuracy and relevance in their outputs.
Analyst
A financial expert who reviews and interprets AI-generated insights.
Analysts ensure the accuracy and relevance of AI outputs, and may intervene to correct or refine the data processed by AI systems. This judgment layer ensures explainability.
AI Validator
AI Validators are designed to check and confirm the accuracy and reliability of data processed by other AI models.
They act as a quality control, ensuring that outputs for example, meet specified standards or comply with regulatory requirements.
Knowledge
The collected information and insights that are stored and continually refined to improve the system's accuracy and efficiency.
It includes data, rules, and interpretations that guide the AI's processes and outputs.
Continuously Improving Models
Continuously improving models refers to the ongoing process of refining AI algorithms based on new data, feedback, and advances in technology.
This ensures that the AI remains effective and relevant in changing environments.
AI Generating AI
AI generating AI refers to AI that produces content or data outputs from given inputs.
These systems leverage deep learning techniques to understand and generate responses, insights, or predictions relevant to user queries or datasets. In a continuous loop these are fed back as inputs to produce better output.
Contextual Representation of Data
Contextual representation of data involves transforming raw data into a format that reflects its semantic relationships and relevance to specific contexts.
This approach helps AI models understand and interpret financial data more effectively.
Faster Implementation
with Less Resources
Through our AI platform, methodology and financial experts.
Unparalleled
Model Accuracy
Through combining experts and AI meaningfully, AI is constantly learning in addition to time / cost savings.
Deeper
Insights
Through building knowledge graphs beyond just one document.
Long-term
Competitive Advantage
Through retaining ownership of your data and models.
Profound Layout Understanding
Elevating language models by providing essential context through advanced Optical Character Recognition (OCR) capabilities and an enhanced table detection system capable of identifying complex table structures for efficient querying.
Precise Language Models
Dedicated - and open-domain - models specifically trained and fine-tuned for the financial industry, which benefit from supervised fine-tuning and reinforcement learning based on human feedback, leading to superior outcomes with leaner models that prioritize privacy.
Hybrid Intelligence
Fostering a meaningful collaboration between AI and subject matter experts. This synergy is facilitated through a seamless user experience, a vast library of use-case-specific applications, and a flexible cooperation model that may include teaching modes or sporadic validation.
Retain Intellectual
Property
IP of fine-tuned AI models and generated training data is owned and only accessible by you.
Privacy
By Design
Our platform supports on-premise or private/hybrid cloud deployments and complies with GDPR.
Auditability
It supports the Federal Reserve’s guidance on model risk management (SR Letter 11-7) & Datenschutzkonferenz recommendations regarding technical and organizational measures for the development and operation of AI systems.
Fireside Chat at AI Week Frankfurt 2024: Key Takeaways
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