Get started with AI using a Virtual Expert
Generative AI (GenAI) solutions can seem so all-encompassing and innovative that it can be difficult to know where to begin with them. Almost every aspect of modern business analytics and workflow is being revolutionized by this unique and transformative technology.
At Evalueserve, we’ve addressed this dilemma by shaping two specialized uses of GenAI: virtual experts and document completion tools. We’ll discuss the latter soon in a companion post. For now, let’s consider two case studies of virtual experts, find out what they’re for, and how they can contribute to your workflow and data analysis.
What is a virtual assistant?
You might be familiar with the earliest iterations of these tools: chatbots. Generative AI systems supercharged chatbot capabilities, adding subtlety, character, and a vastly expanded repertoire of responses. Where once chatbot replies were stock, generic, and often made no sense, AI-powered virtual assistants, such as those developed by Evalueserve, can now essentially replace human interlocutors in many support and enquiry situations.
But virtual assistants have uses deeper and more wide-ranging than merely being super-chatbots. They can be research assistants and BI analysts, effectively. Let’s break down those use cases in more detail:
Research Assistance:
Virtual Assistants can query both structured and unstructured text-based data sources for market and competitive intelligence, business development insights and deal origination.
Business Intelligence:
Virtual Assistants can query structured data sources and create compelling and informative visualizations including dashboards, reports, and financial comparisons.
Both use cases benefit private companies and public non-profit organizations alike, since the universal need of all such corporate entities share is accurate information, and the ability to device actionable insights from it.
Case Study 1: A Virtual Expert built on top of an insight platform
Our M&CI (markets and competitive intelligence) virtual expert has been built on top of our celebrated Insightsfirst platform to act as a portal to laser-focused analysis. The platform uses APIs to connect to a public LLM (large language model), then takes prompts from users to pull domain-specific curated information from unstructured, external data sources.
The virtual expert works even without requiring precise taxonomic tagging. The LLM understands queries that are clearly phrased but requires no specific query format. This renders it much more intuitive to use and delivers more reliable results.
Other benefits include:
- The virtual expert can be trained on highly focused, domain-specific, datasets.
- Usable insights are generated at speed and are presented clearly.
- Response parameters can be refined, based on timeframe, specific competitors etc.
- References and deep links are provided, to evidence insights.
- The tool can also be used for meta-analyses, clustering data from multiple sources, and summarizing thematic insights.
Our virtual expert is an assistant that can derive clarity from structured or unstructured data, shaping the information to provide only the insights our clients require, saving time and clarifying research outcomes.
Case Study 2: A Virtual Expert built into an existing dashboard
There are other ways to incorporate virtual AI GenAI assistants too. They can be plugged into existing data dashboards, providing an instantly invaluable tool for decision-makers.
For instance, a global philanthropic organization wanted access to accurate large-scale health data to inform its work. Their need went far beyond reinforcing business supremacy; in this case, access to accurate data and insights could have life-saving consequences.
Evalueserve incorporated a virtual expert into their data dashboard; one which would accept plain language queries and return accurate aggregated data in real time.
Additional benefits of the virtual expert included:
- Instant access to multiple datasets, not simply that ordinarily displayed on the organization’s data dashboard.
- Mobile access, providing information to employees on the go, keeping remote and hybrid workers informed and in touch.
- External integration with Google and Wikipedia, allowing for up-to-the-minute input from these globally familiar information sources.
Having this virtual expert at their fingertips gave Evalueserve’s client the confidence that decision-making would be fully informed by accurate data.
Conclusion
In conclusion, the expansive potential of Generative AI (GenAI) solutions may initially appear overwhelming, leaving many unsure of where to start. However, using a virtual expert for accessible insights for faster, better decisions is a great place to start.
