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TEXT ANALYTICS

Text analytics combines a set of machine learning, statistical, and linguistic techniques to process large volumes of unstructured text or text that does not have a predefined format to derive insights and patterns. It enables businesses, governments, researchers, and media to exploit the enormous content at their disposal for making crucial decisions. Text analytics comprises a variety of techniques including sentiment analysis, topic modelling, named entity recognition, term frequency, and event extraction.

Winner: Data Conversion Laboratory

Access Innovations
Capacity
 Franz
IntraFind
Megaputer
NiCE
Northern Light Group
Oracle
Pingar
SAS
Squirro
Verint


VECTOR DATABASE

A vector database can be a critical tool for KM by transforming unstructured data such as text or images into numerical vectors (embeddings) and storing them for efficient similarity searches. This gives KM systems the ability to retrieve information based on meaning and context, not just  keywords, by finding semantically similar data. Vector databases are crucial for AI applications such as generative AI and chatbots— providing external, reliable knowledgebases to prevent hallucinations and return trustworthy information.

Winner: MongoDB

Airbyte
Databricks
Elastic
KX
OpenSearch
Pinecone
Qdrant
Salesforce
Vespa.ai
Weaviate
Zilliz


WORKFLOW AUTOMATION

Workflow automation software puts an end to productivity-inhibiting distracting, repetitive tasks and increases efficiency and communication by creating predefined rules, sequences, and actions. Workflow automation improves agile workflows and decreases the need for manual intervention, reducing errors and saving time for critical tasks. The tool promotes better teamwork and communication, speeds up task completion, and improves transparency and accountability.

Winner: Nintex

Adobe
Apryse
Crawford Technologies
KDAN Mobile
KnowledgeLake
Kodak Alaris
Laserfiche
M-Files
Microsoft
Quark
ServiceNow
Zoho

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