Data analysts reportedly spent 30% of time on ad-hoc questions and generating reports, while business users could wait up to 2 days for simple answers.
Simply ask your questions in natural language. SMAQ will understand your questions, translate them and present the results in interactive tables and charts. Skip coding and discover a new way to explore and visualize data effortlessly!
Simply specify your topic and area of interest, and SMAQ will automatically generate pertinent charts along with actionable insights, streamlining your data analysis process.
Leverage the power of context-aware AI to transform questions into code instantly with SMAQ. This tool streamlines the process of writing queries, saving you valuable time by eliminating the need to sift through schema and find the appropriate tables.
Do you often have follow-up questions while reviewing reports and dashboards? SMAQ offers an ideal chat interface designed to address any ad-hoc queries you might have. Get instant answers and deeper insights directly through our interactive platform.
Reuse your existing queries and views (especially complex ones!) SMAQ can refer to them and give more reliable results.
- Everyone must learn to code
- Data and insights confined within the technical team
- Up to 2 business days of waiting for data
- Overloaded data analysts handling ad-hoc requests
- Everyone can analyze data without technical skills
- Immediate insights. Skip the wait!
- Empower users to make more data driven decisions
- Data team can work on more valuable tasks
The member company of Incubation Programme, HKSTP
What is SMAQ?
SMAQ, is an advanced AI tool designed to empower non-technical users to seamlessly interact with data through natural language. With SMAQ, users can effortlessly chat with their data, create visualizations, and construct dashboards using intuitive language, eliminating the need for complex technical expertise. Our mission is to democratize data access and analysis, enabling individuals across all levels of expertise to derive meaningful insights and make informed decisions.
How does SMAQ work?
SMAQ uses generative AI to translate your questions into database queries, retrieve the data from your database and present the result in interactive charts and tables. It can also pick up concepts from your business such that it can answer questions with specific terms and reference.
Does SMAQ save a copy of my data?
SMAQ will never save your data. It only translate user questions into query language. All computation happens in your cloud/server. It only requires READ access to your data source. However, in order to achieve the best translation performance, SMAQ will ask for your consent to save the data schema and up to 5 sample values in each data field. For more, please email info@common-analytics.com
What is RAG?
Retrieve-Augment-Generate (RAG) Framework
- Retrieve: The first step involves retrieving relevant information from a large corpus of text, such as web articles or documents. This is typically done using a search engine or an information retrieval system. The retrieved documents act as a knowledge base for the subsequent steps.
- Augment: After retrieving relevant documents, the next step is to augment this information. This involves extracting key facts, concepts, or entities from the retrieved text. These augmentations help in organizing and structuring the retrieved knowledge, making it easier for the system to generate coherent and contextually relevant responses.
- Generate: The final step is the generation of natural language text based on the augmented knowledge. This can include tasks like answering questions, summarizing information, or even creative text generation. By combining the retrieved knowledge with the augmented context, the generated text is more informative and contextually appropriate.
RAG is a powerful framework used in various natural language processing applications, such as question-answering systems, chatbots, and content generation, as it leverages both existing knowledge and the ability to generate human-like text, resulting in more accurate and context-aware responses.
How do you ensure data security and privacy?
Deployment on AWS Cloud
Our service is deployed on the AWS cloud platform, renowned for its robust security measures, including encryption and stringent access controls.
OpenAI API Integration
OpenAI assures that data sent to their API platform will not be utilized for model training, ensuring the confidentiality of user information. For more please visit – https://openai.com/enterprise-privacy
Audit Trail – Transparent Data Usage
SMAQ implements extensive logging of all data exchanges for thorough record-keeping and monitoring. Regular spot checks and dashboard monitoring enable quick detection of any unauthorized data transmission. We provide full disclosure of data sent to external endpoints to support features, and users can enable or disable specific features to control data exposure.
Data Protection – Adherence to Client Policies
SMAQ strictly adheres to client data access policies, such as policy tags on GCP or other database access controls, ensuring alignment with established security protocols.
Configurable Features for Minimized Exposure
Our platform offers configurable features to empower users in minimizing data exposure risks. For instance, users can easily disable SMAQ visibility for certain columns and tables within the schema, even if they lack expertise in creating database access policies.
How do I get started?
The software is in private beta now. Email info@common-analytics.com if you are interested!
Have more questions?
We welcome any kind of questions that is related to our product. Feel free to contact us at info@common-analytics.com.