Interview Questions for Christopher Wells, Research and Development Vice President at Indico Data
In the world of business intelligence (BI), artificial intelligence (AI) and machine learning (ML) are revolutionising the way unstructured data is handled. These technologies are automating data classification, extracting meaningful metadata, enabling semantic understanding, and integrating diverse data types to improve insights.
Indico Data, a Boston-based startup, is at the forefront of this revolution. Christopher Wells, the vice president of research and development at Indico Data, defines unstructured data as any data that is not easily or usefully represented in a spreadsheet. Indico Data uses AI and ML to give structure and meaning to this unstructured data.
Their approach to explainability is practical and actionable. Instead of just providing high-level statistics, Indico's models and workflows allow users to represent their unstructured data in structured ways that are meaningful to them. This enables users to find specific language in unstructured data, such as the removal of LIBOR as an interest rate benchmark. With Indico, users can filter the answers to their queries by counterparties, date ranges, or other appropriate criteria.
AI systems automatically analyse unstructured data such as text, images, and videos to generate rich metadata including entities, topics, sentiment, and semantic relationships. Natural Language Processing (NLP) extracts relevant insights from text documents, while computer vision interprets visual data. This automation reduces manual effort by up to 90% and improves accuracy by continuously learning from user feedback and adapting to domain-specific language.
Unstructured content is converted into high-dimensional vector representations that capture semantic meaning, enabling searches based on concepts rather than exact keywords. This allows BI systems to retrieve contextually relevant information, perform intelligent document searches, and support advanced knowledge management.
Moreover, ML models link unstructured sources like customer reviews, support tickets, and social media mentions with structured customer data, creating comprehensive customer profiles that enhance personalisation, marketing, and retention strategies. AI can also interpret diverse unstructured formats such as handwritten notes, emails, images, or audio transcripts by extracting and converting them into text or structured data formats suitable for BI analysis.
By integrating ML with BI, unstructured data can inform predictive models that assess risks and recommend preventive measures, leading to better operational efficiency and safer practices. AI continuously analyses unstructured data to provide real-time summaries, quality scoring, and relationship mapping across data sets, accelerating business decision processes.
Unfortunately, the costs associated with unstructured data are significant. They include storage and management, costs of unstructured data in motion, costs of automation for workflows driven by unstructured data, and risks due to incomplete representation of data. However, Indico's solutions aim to address these challenges, making business intelligence possible with unstructured data.
In conclusion, AI and ML are transforming unstructured data into actionable, searchable, and semantically rich information. This capability has become especially valuable in sectors like financial services, where high volumes of diverse unstructured data traditionally hinder analysis. With Indico Data's innovative solutions, businesses can harness the power of unstructured data to make informed decisions, improve operations, and stay ahead in today's competitive landscape.
[1] Indico Data Solutions, (2021). Indico Data Solutions [2] Gartner, (2019). Gartner Reports Only 20% of AI-Enabled Projects Reach Deployment [3] IBM, (2021). IBM Watson [4] Microsoft, (2021). Microsoft Azure [5] McKinsey & Company, (2020). The dawn of the AI-powered investment manager
- Indico Data, a Boston-based startup, leverages artificial intelligence (AI) and machine learning (ML) to give structure and meaning to unstructured data, revolutionizing business intelligence (BI).
- AI and ML automate the analysis of unstructured data such as text, images, and videos, generating rich metadata like entities, topics, sentiment, and semantic relationships.
- With Indico Data's solutions, businesses can filter answers to queries by counterparties, date ranges, or other appropriate criteria, improving operations and staying competitive.
- By integrating ML with BI, unstructured data can inform predictive models that assess risks, recommend preventive measures, and contribute to better operational efficiency and safer practices.
