Introduction

In the era of digital transformation, the ability to understand and leverage complex business data is crucial for success. This is particularly challenging for entrepreneurs from diverse backgrounds who may not have extensive experience in data analysis. Natural Language Interfaces (NLI) are emerging as a powerful tool to democratise access to data, making it comprehensible and attainable for everyone¹.

Harnessing Data, Simplifying Structures

NLI serves as a catalyst for efficient interaction with complex business data. It allows users to engage in a conversational manner, making data querying more intuitive². According to a report by Deloitte, a staggering 58% of business leaders identify NLI as a game-changing technology for their organisations over the next two years³. The power of NLI lies in its ability to make data more accessible, breaking down the barriers of complex data structures and supporting informed decision-making.

Promoting Accuracy and Consistency

Misinterpretation of data can lead to costly mistakes. NLI is designed to counter this problem. With its ability to grasp the nuances of language, it provides precise responses to user queries, enhancing data accuracy and consistency. As stated by Tactic, a company specialising in data quality, NLI can curtail data entry errors by up to 30%—a critical factor in enhancing the quality of business decisions⁴.

Elevating User Experience

Beyond the functional benefits, NLI significantly improves user experience. A report by PwC indicates that 72% of business users prefer using NLI over traditional interfaces like spreadsheets and dashboards⁵. By creating a more personalised and engaging experience, NLI boosts user motivation and involvement.

The Valerian NLI Advantage: A Partnership Through Shared Data

At Valerian, our future deployment of NLI represents more than a tech innovation; it’s a commitment to an inclusive partnership that transcends mere funding. Through our AI algorithms, we plan to amalgamate diverse data streams during the funding process, unveiling business insights that benefit our clients both before and after funding⁶.
With NLI, we aim to provide an avenue for clients of all backgrounds to effortlessly interact with their data, unlocking vital insights and enabling informed decisions. This capability aids in business growth while also cementing our role as an embedded partner in our clients’ success stories⁷.
Valerian not only addresses the standard challenges associated with NLI deployment but turns them into strengths. Our robust data infrastructure ensures accuracy and consistency while our dedicated support system empowers users, irrespective of their familiarity with natural language interfaces⁸.
Beyond just providing funding, Valerian facilitates a symbiotic relationship powered by shared data and insights. We work hand in hand with our clients, aligning our growth with theirs, and fostering an environment of mutual success and understanding. This is the unique blend of financial support and actionable Business Intelligence that defines the Valerian advantage⁹.

References:

1. Tewari, G. (2023, July 11). Embracing AI and Natural Language Interfaces. Forbes. Link
2. Desmond, M., Isahagian, V., Muthusamy, V., & Duesterwald, E. (2023). A Natural Language Interface for Building Business Automation Decision Rules. IBM Research. Link
3. Buchholz, S., & Briggs, B. (2019). Tech Trends 2019: Beyond the digital frontier. Deloitte Insights. Link
4. Tactic. (2021). Product Update: Improve Your Data Quality Using Natural Language Processing. Link
5. PwC. (2019). Technology Trends 2019. Link
6. VentureBeat. (2021). How NLP is turbocharging business intelligence. Link
7. Affolter, K., Stockinger, K., & Bernstein, A. (2019). A Comparative Survey of Recent Natural Language Interfaces for Databases. arXiv preprint arXiv:1906.08990. Link
8. Damljanovic, D., Agatonovic, M., & Cunningham, H. (2010). Natural Language Interfaces to Ontologies: Combining Syntactic Analysis and Ontology-Based Lookup through the User Interaction. In: Aroyo, L., et al. The Semantic Web: Research and Applications. ESWC 2010. Lecture Notes in Computer Science, vol 6088. Springer, Berlin, Heidelberg. Link
9. Affolter, K., Stockinger, K., & Bernstein, A. (2019). A Comparative Survey of Recent Natural Language Interfaces for Databases. arXiv preprint arXiv:1906.08990. Link