BITVORE WHITE PAPER

A Guide to Converting Unstructured Data into Actionable ESG Scoring

Unstructured data sources can provide an important view of how a company adheres to Environmental, Social, and Governance (ESG) standards. Developing a Natural Language model to identify ESG content and events is an essential step which requires a collaborative effort. This white paper shares some key lessons learned and provide guidance on how to create and tune a Natural Language model to detect ESG events from unstructured data sets.

BITVORE WHITE PAPER

Tractable Understanding of the World Using AI + NLP

Learn how AI/NLP analysis of the world’s unstructured textual data provides analysis, trending, correlation, and early indicators of fundamental business, industry and market changes and impacts.

BITVORE WHITE PAPER

Use AI to Improve Business Strategy and Emerge a Post-Recession Winner

Focusing on AI technologies that augment your employees’ capacity, mitigate business risks and differentiate you from your competition can drive fundamental value in your business.

BITVORE WHITE PAPER

Bitvore Cellenus Sentiment Scoring

In this white paper, you’ll learn how Bitvore’s sentiment scoring system can be used to improve the decision making processes.

Download and learn:

• What sentiment analysis is and how Bitvore’s proprietary approach works
• The types of sentiment analysis
• How Bitvore sentiment analysis can improve your business results

BITVORE WHITE PAPER

Using AI-Processed News Datasets to Perform Predictive Analytics

Find out if our AI-processed insights from unstructured data were able to predict Amazon’s HQ2 location. Download this whitepaper and learn:

• How we leverage AI to process large datasets to perform predictive analytics.
• How municipal, economic and corporate precision news can drive predictive analytics.
• How we combined our data with outside requirements laid out by Amazon and predictive models to make intelligent predictions.
• Detailed results of our predictions.

BITVORE WHITE PAPER

Unstructured Alternative Data in Predictive Modeling

Data scientists can spend 60-80% of their time gathering sources of unstructured alternative data (alt-data) and preparing it for use in predictive modeling. Download the FAQ and learn:

• What unstructured alt-data is and how it’s used in predictive analytics.
• Why you should be including unstructured alt-data in your business strategy to make more intelligent decisions.
• How most data scientists use alt-data to build predictive models for analysis.
• How Bitvore’s approach differs by enabling us to deliver AI-Ready Data to our customers, saving them 60-80% of their time when analyzing alt-data.