Example of a Proof of Concept (PoC)

Maximilian Schneider

When it comes to efficiently processing documents and unstructured text, artificial intelligence (AI) can add tremendous value. In this blog post, we present a proof of concept (PoC) for implementing an AI-powered document processing system with Konfuzio.

What is a Proof of Concept (PoC)?

A proof of concept is a practical demonstration that shows that an idea, project, or system can work as intended. A PoC can be used to show the feasibility and potential benefits of a new technology before major investments are made. It is an important step in minimizing risk and building confidence in the technology. For more information, see a separate post: What is a proof of concept?

What are the advantages of a PoC?

In the digital business world, mastering unstructured data is often crucial. This is where Konfuzio, a specialized AI solution, offers new perspectives. A proof of concept (PoC) with Konfuzio is not only a safe strategy to put the technology through its paces, but also opens up a clear view of added values and potentials of artificial intelligence in a business context.

Even more than that, early adoption of Konfuzio could position your company as a technology pioneer that keeps its finger on the pulse of innovation. And that's just the beginning: Konfuzio enables you to master regulatory requirements and take your data security to a new level when using AI.

With a PoC, you not only get a glimpse of Konfuzio's capabilities, but also a solid foundation for making decisions about its role in the future of your business. With Konfuzio you open up a world of possibilities - are you ready to explore it?

The PoC process with Konfuzio

When commissioning a PoC with Konfuzio, you will go through the following structured process together with our team of experts:

AI Proof-of-Concept (PoC) Plan2023-07-022023-07-092023-07-162023-07-232023-07-302023-08-062023-08-132023-08-202023-08-272023-09-032023-09-102023-09-172023-09-24Requirement Analysis Success Criteria Data Collection for Training Test Plan Creation Data Analysis Data Security Analysis Operation Setup of the AI Model Training Model Adjustment Test Execution and Evaluation Presentation of Results Review and Adjustment of the PoC Plans Use CaseData Collection and AnalysisData Security Analysis and Operation SetupModel Training and AdjustmentTesting and EvaluationPoC CompletionAI Proof-of-Concept (PoC) Plan
  1. Use case discussion: First, we understand your specific requirements and the desired use case for the PoC. This could be, for example, the analysis of contract documents, credit applications or other unstructured texts.
  2. Definition of success criteria: Prior to the start of the PoC, we establish success criteria that are used to evaluate the performance and utility of the AI system. These could be, for example, the accuracy of extraction, the speed of processing, or other specific metrics.
  3. Data collection and analysis: We jointly identify and collect relevant sample data to train and evaluate the Konfuzio system. These could come from existing documents in your organization or be created specifically for the PoC.
  4. Data security analysis: Data is at the heart of every AI system. Therefore, it is crucial that we ensure that your data is secure throughout the PoC. In this phase, we analyze data security requirements, implement appropriate security measures, and ensure that all activities comply with data protection laws.
  5. Operating setup of the AI: Once we have confirmed that the AI system is working effectively and that data security is guaranteed, we set up the system for operation. This includes setting up the necessary infrastructure, establishing operating and maintenance procedures, and training your team on how to use the system.
  6. Model training and fitting: Our Data Scientists use the collected data to train specific AI models for your requirements. In doing so, we adapt the system to the structure and extraction needs of the relevant documents to achieve the best possible results.
  7. Testing and evaluation: In PoC, we evaluate the system with a representative set of test data and assess the extraction accuracy as well as the workflow. Your feedback during this phase is crucial to further improve the system and adapt it to your requirements.
  8. PoC completion and presentation of results: After testing and evaluating the AI system, we document and present the results. These include an analysis of the system's performance against the defined success criteria and recommendations for the next phase.

This structured approach allows us to ensure that the PoC meets your specific requirements and provides you with clear insight into the capabilities and benefits of AI-powered document processing with Konfuzio.

Technical feasibility vs. professional value

When evaluating and planning an AI project, it is essential to consider both the technical feasibility and business value of the proposed use cases. While technical feasibility focuses on the technological and operational challenges that must be overcome to implement and operate the system, business value focuses on the benefits and value that the system can generate for the business and its customers.

Technical feasibility and professional value are two sides of the same coin and should always be kept in balance. High technical feasibility, for example through the use of advanced AI models, does not necessarily mean high business value if the problems or tasks solved are of little importance to the business. Similarly, a use case with a high business benefit, such as improving customer satisfaction, may miss its full impact if the technical feasibility is not there.

Therefore, when creating a PoC with Konfuzio, it is critical that we work closely with our customers to understand and evaluate both the technical feasibility and business value of each use case. Our goal is to strike a balance between these two aspects that allows us to develop and implement an AI system that is both technically capable and business valuable.

PoC examples and use cases

Artificial intelligence (AI) has found its way into many industries by making unstructured data actionable. Konfuzio, an advanced AI solution, uses algorithms for text analysis and document processing to create added value in areas such as healthcare, finance, retail, transportation and logistics, and the energy sector. Below we take a look at examples of how Konfuzio is revolutionizing these industries and how you can benefit from it.

In the Healthcare Industry the NLP and NLU component of Konfuzio enables deep analysis of medical reports. By using transformer-based algorithms such as BERT, clinical texts can be better understood and relevant information for diagnosis and therapy planning can be extracted.

At Financial sector, especially in the area of fraud detection, deep learning methods such as LSTM (Long Short Term Memory) can be used for sequence detection and anomaly detection. They help identify unusual patterns in unstructured text and transaction data to detect potential fraud.

In the areas Broker pools, insurers and reinsurers Konfuzio's AI offers significant advantages through the use of NLP and NLU algorithms as well as advanced machine learning techniques. Transformer-based models such as BERT and GPT allow in-depth analysis and interpretation of complex insurance documents, claims reports and policy-related texts. They help broker pools extract and process information quickly and efficiently. Insurance companies benefit from automated and accurate risk assessment by applying classification algorithms such as support vector machines (SVMs) or decision trees. In reinsurance, Deep Learning algorithms, especially LSTM, enable the analysis of large, sequential data sets, supporting the identification of loss patterns and risk profiles. Konfuzio represents a key solution in these contexts to increase efficiency and optimize the handling of unstructured data.

For the Retail Konfuzio uses NLP and Deep Learning algorithms for text classification and sentiment analysis. By analyzing customer feedback and product reviews, Konfuzio can develop a deep understanding of customer preferences and generate personalized product recommendations.

In Transport and logistics computer vision is used together with NLP to extract and process information from different document types. By using Convolutional Neural Networks (CNNs) for document classification and Transformer models for text extraction, relevant information can be efficiently extracted from waybills or delivery instructions.

At Energy sector the combination of NLP for text report analysis and time-series forecasting algorithms such as LSTM or ARIMA (AutoRegressive Integrated Moving Average) is particularly relevant. With these methods, Konfuzio can produce forecasts for energy consumption and production and help optimize the operation of the power grid.

In all these scenarios, Konfuzio relies on the combination of NLP, NLU, computer vision and generative AI algorithms to transform unstructured data into valuable information and solve industry-specific challenges.

More information about an AI PoC

If you would like to learn more about the PoC creation process or are interested in working with Konfuzio to improve your document processing, please do not hesitate to contact us. We look forward to discussing your requirements in more detail and setting up a customized PoC for you.

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