Generative AI and Intelligent Document Processing (IDP)

Increase in choices for IDP solutions

There is a growing level of competition as providers who were previously only able to handle structured content, such as forms with defined fields, are now expected to show some capability in processing semi structured and unstructured content, like contract documents, email bodies. This blurs the lines between competitors, making it challenging for organizations to understand a provider's true capabilities.

LLM-enabled IDP products are leading to expansion of features and capabilities

The features and capabilities of LLM-enabled IDP products are expanding rapidly, but they are also creating uncertainty about the importance and usefulness of these new functionalities. IDP products are being improved and enriched with new features utilizing LLMs, including: Assisted writing, Sentiment analysis, Enhanced entity recognition, Semantic search and discovery across document collections, Workflow automation and insight generation using the RAG approach, Document summarization, Enhanced document collections to support training custom LLMs, New interfaces on top of IDP, Access to a plug-in ecosystem via LLM, Natural Language Generation (NLG) to facilitate error correction in extracted data. Consumers are becoming overwhelmed by the expanding features in IDP solutions that use LLMs, leaving them uncertain about which functions are useful and to what extent. This is likely to make sourcing IDP products extremely challenging, especially with the abundance and variety of options in the vendor environment. Ultimately, this could lead to dissatisfaction with IDP product purchases, often raising concerns about "technical debt" and "value for money.";

General-Purpose LLMs will fail to scale due to issues of reliability, trust and costs.

LLMs provide answers based on hallucinations rather than empirical evidence. Their responses are unpredictable and yield different outcomes for the same input. Furthermore, general-purpose LLMs do not cite their information sources, which means they lack provenance. As a result, the dependability of enterprise customers using general-purpose LLMs is greatly diminished. Data and customer-sensitive information are often present in corporate documents. Due to concerns about compliance breaches, exposure of confidential data, and the risk of legal action, corporate clients are reluctant to use general-purpose LLMs. Due to the substantial volume of such documents, the token-based pricing model used by general-purpose LLMs may not be suitable for the enterprise document processing environment. This could significantly impact the cost of the solution. As a result, fine-tuning proprietary (or even open-source) models may prove to be more expensive and require specialized knowledge

Choosing the right IDP solution for large-scale deployments

When looking for IDP solutions, customers should verify the methodology used by IDP providers when using LLMs. Evaluate vendors who only use proprietary general-purpose LLMs from external sources for tactical, low-volume, insensitive, and low-value use cases. Understand the limitations of RAG designs, including dependencies, computing complexity, cost, and trade-offs between accuracy, latency, and training. Also, be mindful of the constraints associated with fine-tuning LLMs, such as interpretability, ethics and bias in trained models, trade-offs between cost and accuracy, and fine-tuning costs.

Kanverse brings you the best-in-class IDP software to process your documents right from ingestion, classification, extraction, validation to filing. Extract data from a wide gamut of documents with up to 99.5% accuracy using its multi-stage AI engine. Kanverse complements its patented multi-stage engine with the latest LLMs. Kanverse is integrated with OpenAI/ChatGPT, Azure OpenAI, Google Gemini, and Anthropic Claude to deliver maximum extraction accuracy possible. Say goodbye to manual entry, reduce cycle time to seconds, optimize cost by up to 80%, minimize human error, and turbocharge productivity of your team.