A technical and non-technical introduction to all-things AutoQL, including everything you need to get started and successfully implement AutoQL in your enterprise.
These docs contain a full overview of the steps you'll take to begin delivering state-of-the-art conversational data experiences in you enterprise, or in your own software. In this section, you'll learn about our company and be introduced to our flagship solution offering, AutoQL.
On this page:
- Introduction to Chata.ai
- What is AutoQL?
- What does AutoQL do?
- Who is AutoQL for?
- Integrators, Customers & End Users
Introduction to Chata.ai
Based in Calgary, Canada, the team behind Chata.ai is a passionate group of data scientists, engineers, developers, and data-obsessed nerds working hard to transform the way people interact with, experience, and leverage their data. Our leadership is backed by decades of experience innovating in the tech, healthcare, and finance industries.
Our vision is a future where humans communicate with computers the same way they do with other humans. We build conversational AI technologies that close the gap between humans and their data by facilitating the dynamic translation of natural language to database query language. Our flagship solution — AutoQL — enables software providers to deliver conversational data access through natural language within their existing software applications.
What is AutoQL?
AutoQL is a solution that translates business questions to insights. It is an embeddable conversational AI solution for database access that fundamentally transforms the way humans interact with their data. At its core, our technology enables the dynamic translation of natural language to database query language(s).
By making databases accessible through natural language, our customers are able to drastically reduce demands on internal resources, mitigate the need to bridge workflows to third-party business analysis tools, and offer unparalleled data experiences to their business users.
What does AutoQL do?
AutoQL enables the dynamic translation of natural language (NL) to database query language, making it possible deliver state-of-the-art conversational data experiences in modern enterprises. With AutoQL, business users can interact seamlessly with their data simply by asking questions in their own words.
Using proprietary technology in the data generation, Natural Language Understanding (NLU), and query generation areas, AutoQL is a powerful API-first solution that can be implemented and adopted in a myriad of different ways. We provide flexible open-source widgets (including Data Messenger, Data Alerts, and Dashboards) that can be customized and embedded into any branded or proprietary software application or web portal system, a robust web application that can be white-labelled to suit your brand preferences, as well as direct integrations with Microsoft Teams and Excel to support individuals in getting work done where they're already at.
Learn more about our technology and how the AutoQL system works.
Who is AutoQL for?
AutoQL is for enterprise companies, software application providers and web portal developers who are looking to deliver state-of-the-art conversational data experiences and democratize access to data. Modern businesses aim to deliver powerful user experiences and ultimately want people to be successful within the systems they’ve built. But when it comes to getting data out of applications and warehouses, built-in reporting options and datasets are often rigid, inaccessible, or non-comprehensive.
AutoQL gives non-technical business users the ability to search, access, and analyze data using natural language (or put more simply, ask questions in their own words to get important information). We call this a Conversational Data Experience.
What is a Conversational Data Experience?
A conversational data experience is a dynamic interaction between a person and a database that closely mimics the intuitive way humans are accustomed to finding and exploring information in the real world: through natural language.
While graphical user interfaces and use of specialized programming languages (database querying languages) are typical methods for accessing and analyzing data, a conversational data experience leverages innovative AI technologies to enable users to "just ask" for the data they are seeking using natural language — the same way they might ask another human — and receive the relevant data as a response.
Integrators, Customers & End Users
Conversational data experiences break down the barriers between users and databases, empowering people to independently search, access, and analyze their data, all from their current or existing workflow. Through AutoQL, enterprises and software providers can empower their teams, their customers, and their users with the exceptional digital experiences they demand and the data access they need.
To help with understanding, it’s important to establish commonly understood terminology:
- At Chata.ai, Integrators are enterprise companies, software application developers or other solution providers that implement AutoQL in their application.
- Learn more about AutoQL for Integrators here.
In cases where Integrators develop and sell their software application to other businesses, we refer to these businesses as Customers.
- A Customer refers to a business or group that uses a software application that is made available by an Integrator.
- Learn more about AutoQL for your Customers here.
Customers are the high-level entity (the business) that purchases an Integrator's application and makes that solution available to End Users within their own company and/or to their external users. Thus, any individual who uses the software that is built by an Integrator is described as an End User (User).
- An End User (User) is any person who engages with/has access to the AutoQL, that is made available by an Integrator.
- Learn more about AutoQL for your End Users here.
Updated 3 months ago