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Description
Tailor your outreach efforts to engage consumers on a personal level, leveraging insights from behavioral economics and domain-specific generative AI. Our innovative multi-armed bandit technique significantly enhances outcomes when compared to standard A/B testing methods. It offers seamless plug-and-play integration, is cloud-based, and adheres to SOC 2 Type 2 security standards. The advanced multi-variate reinforcement learning approach of our AI facilitates the swift identification of optimal strategies, contrasting sharply with conventional testing processes. By examining a broader range of variables than traditional champion/challenger methods, our AI accelerates the time to value and streamlines the elimination of ineffective strategies, leading to faster insights. Moreover, our system identifies the most effective treatments tailored to each customer segment. To ensure the ongoing protection of our clients' data, we collaborate with an independent auditor to uphold a SOC 2 report, providing an objective certification of our security measures. This rigorous approach not only enhances our credibility but also reinforces our commitment to safeguarding customer information.
Description
NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.
API Access
Has API
API Access
Has API
Integrations
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau
Integrations
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
KredosAi
Country
United States
Website
www.kredosai.com
Vendor Details
Company Name
NetOwl
Founded
1996
Country
United States
Website
www.netowl.com/name-matching-software
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Product Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
