Generative AI in Insightsfirst: Pioneering and Scaling Opportunity Identification
Large consulting and advisory firms use Evalueserve's SaaS-based platform Insightsfirst Opportunity Radar (ORAD) and domain experts for their opportunity and deal intelligence programs. Insightsfirst enables users to identify opportunities that align with their specific mandates, such as discovering high-growth companies in a particular sector, pinpointing potentially distressed companies in a region, or recognizing firms needing procurement services.
Each company’s mandate is unique, requiring some level of configuration towards its use case. What sets Insightsfirst ORAD apart is its ability to meet this need and provide curated and targeted leads while remaining a SaaS-based product. Generative-AI-powered Insightsfirst identifies opportunities through a unique trigger-based approach defined by a configurable mind map.
Each mind map is developed with a well-defined set of triggers, sub-triggers, and keywords, created in consultation with clients and their requirements. These triggers feed into the AI engine, which then helps shortlist opportunities.
For the past 2-3 years, we have supported firms in their opportunity intelligence programs by utilizing AI as part of the back-end engines that identify, shortlist, and summarize opportunities. In 2022, we integrated Large Language Models (LLMs) into our back-end workflow engines.
For example, we employed OpenAI language models at two stages of the trigger pipelines:
- News segmentation into "relevant" and "irrelevant" categories, with the model trained on historical examples of segments that have been accepted or rejected.
- Auto-summarization of clusters of news segments about a specific company.
Incorporating OpenAI LLMs into the back-end engines has led to a more accurate and cost-effective Opportunity Identification Engine. Benefits have included reducing data noise, eliminating irrelevant information, and speeding up the results analysis process. LLMs have also provided concise summaries of news clusters, allowing analysts to quickly assess the relevance of a cluster and identify essential information.
Bringing Generative AI to the Front-End of the User Experience
Over the last few months, the rapid growth and interest in Generative AI has made it clear this technology is here to stay. As we witness the exponential increase in user engagement and developer community involvement with platforms like ChatGPT, it's evident that this technology will transform how we interact with the world.
Consider Chat GPT's dynamic growth to reach one million users compared to other groundbreaking platforms:
- Netflix (1999) took 3.5 years
- Facebook (2004) took ten months
- ChatGPT (2022) took 5 days
It is estimated that ChatGPT surpassed 1 million users in just five days!!! Users find conversational technology compelling and valuable, and if harnessed well with strong use cases, it can serve enterprise customers, too.
Let's explore how Evalueserve is leveraging Generative AI algorithms to enhance user experience on our Insightsfirst platform and our plans for the future.
The Birth of Research Bot on Insightsfirst
About a month ago, we introduced the Research Bot as a conversational chatbot microservice powered by generative AI that can be plugged into platforms like Insightsfirst. The chatbot allows users to query content in a human-like manner, enabling them to ask unstructured questions.
Research Bot is backed by large language models (LLMs) and is trained on proprietary domain-specific data, ensuring the relevancy, accuracy, and removal of bias in the results. We also pointed the Generative AI engine to domain-specific content into Insightsfirst ORAD. This multipronged approach allows users to leverage Generative AI though out the platform. The table below illustrates our Insightsfirst implementation.
Expanding Generative AI Capabilities to Insightsfirst Opportunity Radar
Generative AI technology in Insightsfirst ORAD allows users to leverage its power in multiple ways, as can be seen in the adjoining image. These include:
- Querying curated content that resides on the platform. This is clean content that is curated by AI and domain-experts
- Searching semi-curated content created by the AI engine. This does not include any analyst intervention and allows for more scale to include a larger subset of companies.
- Allowing users to find quick leads via the conversational chatbot by asking unstructured queries
Experimenting with Autonomous Agents, such as AutoGPT – A Future User Engagement
Another compelling technology is autonomous bots, such as AutoGPT, an AI agent created with ChatGPT that breaks down goals or objectives into smaller tasks. One query only is required to accomplish the end goal, and there is no need to define dependencies or critical pieces to achieve the larger objective.
We are actively experimenting with this technology and seek to integrate it into our platform by the end of the third quarter. By leveraging autonomous bots in an enterprise use case, users can use a single prompt to obtain company overviews or executive profiles quickly.
The Advantages and Future of Generative AI
Our approach to leveraging Generative AI offers numerous benefits to enterprise users:
- Utilizing the best large language models
- Building pre-defined prompts to ensure contextualized domain-specific results
- Focusing on domain-specific content for recency and accuracy
- Constantly evolving to cater to the latest developments in Generative AI
It's important to remember that Generative AI-based tools produce results that can be subjective and not always comprehensive. They should be used as a starting point or for quick, directional information, especially when they are trained on enterprise and domain-specific data. Ultimately, the critical value lies in the judgment of the analyst or consultant.
Want to learn more about what we're doing? Reach out, and let's start a conversation.
