Enterprise Knowledge Platform for Unstructured Data Automation

Elevate your financial operations with Hybrid Intelligence


Among Other Clients, We Serve


Global ratings



Of the largest
US banks


German insurance

Your Challenge

Today the financial sector faces a significant challenge with the increasing volumes of unstructured data found in credit agreements, SEC filings, ESG reports, and other complex documents. Traditional methods, often manual and inefficient, struggle to extract and utilize relevant data from diverse formats for analysis and further downstream processing.

Your Solution

Our award-winning Enterprise Knowledge platform streamlines the document automation process, helping you easily customize workflows and generate insights that fuel your team with valuable training data. Efficiently engineer AI models into these workflows to maximize optimization–our system automatically evaluates model results over test data sets and production. Our advanced AI models, pre-trained for a multitude of financial scenarios, redefine the standards of data automation.

Request a demo

How the Enterprise Knowledge Platform Works

Rooted in a deep understanding of AI and Finance
mathodology work


Sourcefast 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.


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.


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.

Model Accuracy

Through combining experts and AI meaningfully, AI is constantly learning in addition to time / cost savings.


Through building knowledge graphs beyond just one document.

Competitive Advantage

Through retaining ownership of your data and models.

Advanced AI-driven Document Automation
for Financial Organizations

By combining various AI models such as knowledge graphs, precise language models, and advanced table detection, we’ve created a proprietary, use-case-agnostic solution, specifically designed for the financial domain. This combination not only understands complex financial terminology but also respects the nuances of privacy and compliance, ensuring accurate, actionable insights, and leaving the final decision to the financial experts through state-of-the-art user interfaces. Our solution helps financial service firms continuously improve daily document automation for the entire organization.
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.

Spatial Intelligence

Our spatial intelligence capabilities enable unparalleled insights into complex document layouts, offering profound layout understanding. By prioritizing privacy, our in-depth layout comprehension models, trained on millions of industry-specific documents, surpass generalized models.

This unique combination of industry-leading accuracy and data protection positions our spatial intelligence solutions at the forefront of innovation, transforming the way financial companies interact with their critical information.

Hybrid Intelligence Methodology

Transformative Productivity Through Human-AI Collaboration

Hybrid intelligence puts your experts at the center of the automation process, enabling them to gain immediate efficiency while generating domain-specific training data to improve automation efforts.

Seamless experience for subject matter experts
Fully customizable, familiar user experience

Large library of use case-dedicated applications
Large library of use case-dedicated apps

Best cooperation model between AI & humans for a specific task
Easily manageable, secure, & scalable

Learn Why Top Financial Companies Use the Enterprise Knowledge Platform


In the intricate domain of credit lending, a leading US bank aimed to redefine its approach to automating the extraction and improving the downstream analysis of vast amounts of unstructured data.


In the fast-paced world of international transportation finance, precision and speed in document processing are paramount. A European bank faced these challenges head-on, seeking intelligent document processing (IDP) solutions.

Leading AI Privacy, Security, & Trust: Powerful Compliance & Control Features Built-in

AI systems raise issues with regulatory compliance and trust preservation, while the need for clear AI decision explanations and strong data security measures, particularly under GDPR, highlights the importance of robust AI and data protection strategies. As Cognaize advances AI document automation in finance, we address these challenges with effective risk mitigation strategies for responsible and secure AI applications.
Retain Intellectual

IP of fine-tuned AI models and generated training data is owned and only accessible by you.

By Design

Our platform supports on-premise or private/hybrid cloud deployments and complies with GDPR.


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.


Learn how we can help you with our platform

See how you can access unparalleled accuracy and speed in financial document processing for financial service firms.

Step 1: Start a Conversation

Please feel free to contact us regarding any inquiries or just to start a conversation.


Document automation simplified

News & Insights

Stay on top of the latest developments in AI, hybrid intelligence, and document automation.
Cognaize Wins AIFinTech 100 Award as Trailblazing Company Transforming Financial Services
Cognaize wins AIFinTech 100 Award

Cognaize Wins AIFinTech 100 Award as Trailblazing Company Transforming Financial Services

Jun 19, 2024 9:03:54 AM 2 min read
Addressing AI’s Energy Problem: How Cognaize is Leading the Way
Addressing AI’s Energy Problem: How Cognaize is Leading the Way

Addressing AI’s Energy Problem: How Cognaize is Leading the Way

Jun 17, 2024 6:03:30 AM 2 min read
Advancing AI Reasoning: The Synergy Between Knowledge Graphs and Large Language Models

Advancing AI Reasoning: The Synergy Between Knowledge Graphs and Large Language Models

Jun 3, 2024 8:26:51 AM 3 min read

Never Miss a Story