🔮TALKdata
A revolutionary capability to get real-time answers to your business questions.
Advancements in Large Language Models, combined with Clarista's unique Semantic Data Fabric, empowers users to get real-time answers to their questions. No more sending email requests to your staff and waiting for days to get your answer back.
Generative AI
Generative Artificial Intelligence (GenAI) is a specialized field in Artificial Intelligence, that utilizes millions of samples of written text, images and videos to train AI models, which can then be used to generate new text, images and videos. ChatGPT (Generative Pre-Training Transformer) is an example of how this exciting field of AI can help us in getting answers to our questions, based on pre-trained models.
Clarista TALKdata
Clarista TALKdata leverages a six step process to bring real-time answers to business questions:
Interpretation: If the question has never been asked before, Clarista identifies how to best answer the question, from the information available to its Semantic Data Fabric.
Semantic Data Query: Clarista then construct a meta-data query using using the identified data sets and business terms published to its Semantic Data Fabric
Technical Data Queries: In this step, Clarista converts the meta-data query into series of technical data queries to fetch the required data real-time from one of many sources.
Results Compilation: Once the results of each technical query are retrieved, they are then joined and aggregated to answer user's question
Results Rendering: Identify the best format(s) suitable to show the answer of the query to the user - charts, KPI, tables etc.
Adaptive Learning: Clarista leverages a proprietary AI learning algorithm, to learn based on user's feedback on the results. This helps in optimizing the results for each customer over time.
GenAI adds yet another capability to Clarista's Data Fabric architecture, and utilizes several other components such as Distributed Queries, Semantic Engine and AI Learning Algorithms to provide a seamless experience to its users.
TALKdata does not stop with getting real-time answers. It has several additional features to share TALKdata sessions with colleagues and to ask for help or verification from Data Teams, when required.
Key Features:
Ability to speak or enter questions in natural speaking language
Get real-time answers to your in best format based on the data returned
Transparency into the datasets, data terms and queries utilized to answer the question
Ability to drill-through underlying data sets to verify
Ability to collaborate with multiple users in a TALKdata session
Ability to save a session with multiple questions as a report.
Ability to request for Data Team's help for complex questions when needed
Ability to track any answer (chart, KPI or table) in a personalized Track-Board (see next section for more details)
Ability to provide feedback on answers, to optimize the responses for your colleagues.
How is TALKdata different from other GenAI tools?
Ease of use, security, speed, collaboration and accuracy are just few of the features that stands out in comparison to other tools that claim to provide similar capabilities. Clarista didn't have to design a new architecture to add this unique feature to its software. It already had the benefits of its Semantic Data Fabric, that maps all technical data into well-organized and defined business terminology. Hence Clarista was able to leverage this semantics layer and distributed computing technology to get real-time answers to user's questions, irrespective of where the data sits. Most competitive products struggle to solve the translation and technical query execution problem.
Secondly, Clarista goes beyond the interpretability of a Large Language Model, by creating another layer of intelligence based on customers' feedback to the answers it provides. By having the 'Data Expert in the Loop' concept, Customer's Data Experts can be invited by the business users to any TALKdata session to further verify the results. Any changes suggested by the Data Experts is automatically incorporated into a learning algorithm, that further improves the accuracy of results for each customer.
Security remains a key concern for many enterprises in using open source large language models such as OpenAI. While they want to avail the exciting opportunities made possible by such technology, they want to do so in the most secured and compliant manner. Clarista ensures the strictest security controls, by never sharing any customer data with any Large Language Model. Even the technical details such as system names and data tables are hidden. Clarista only interacts with the LLMs through its semantic engine and handles the translation of semantics to technical details in a dedicated and secured customer instance. In addition, customers can also utilize other Clarista features such as sensitive data masking and role-based access controls to further restrict access to data as needed.
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