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Frequently Asked Questions

Top FAQs

Getting Started

How AutoQL Works

Querying with AutoQL

Implementation Options

Partner Ecosystem

AutoQL Pricing

Privacy & Security

Resources & Support

Top AutoQL FAQs


1) What is AutoQL?

AutoQL is an API-first solution that simplifies data access and streamlines analysis by making data accessible to everyone — even non-technical business users — through natural language.

2) Why use AutoQL?

Everyone needs access to data to make informed decisions and take strategic action. We believe getting answers and information from a database should (and can) be as simple as having a conversation. So, we built AutoQL to help people access their data in a more intuitive way.

AutoQL enables business users to access data in real time, simply by asking questions in their own words so they can get answers sooner, and take action, faster.

3) What makes AutoQL unique?

With AutoQL, any user can simply ask questions in their own words to access and analyze their data. Through our API, AutoQL receives, understands, and interprets natural language queries, dynamically generates a corresponding database query language statement, executes the DBQL statement against the database through a read-only connection, and returns relevant data to the end user within seconds.

4) Why implement AutoQL in my software or enterprise solution?

By implementing AutoQL in your solution, you can expect to:  

  • Boost revenue, attract new users, and add value for your existing loyal customers.
  • Stand out in your market with cutting-edge AI technology that drives value for every user.
  • Save on costs by significantly reducing incoming support tickets and ad hoc reporting requests. 
  • Leverage your skilled team and internal resources for high-value, revenue-generating projects.
  • Gain an edge over competitors offering limited or rigid data access and reporting options.  
  • Keep users engaged in your app instead of losing them to third-party BI tools.

5) Is AutoQL a SaaS application?

No, AutoQL is not a SaaS application. It is an API that dynamically translates natural language to database query languages. This API-first approach allows for broad flexibility in how AutoQL can be implemented. We support fully-embeddable and customizable widget options for software teams, and accessible interfaces (like our app for Microsoft Teams) for enterprise use cases.

6) Is AutoQL a business intelligence (BI) tool?

AutoQL is a dynamic API-first solution that supports a wide range of use cases, including self-service analytics, ad hoc reporting, and exploratory analysis.

By implementing AutoQL, businesses are empowered to democratize, support, and promote data-driven workflows by enabling their audience (users, employees, or other) to access and explore their data using natural language.

AutoQL can be embedded within an existing software for self-service ad hoc reporting and enhanced analytics capabilities, or it can be leveraged as a powerful addition to an existing BI stack.

Because AutoQL is an API, we have the flexibility and ability to integrate with any BI tools/systems that allow third-party APIs to be called from their systems.

7) Can AutoQL be embedded in my existing software or portal?

Absolutely! AutoQL is an API-first solution, so it can be embedded natively within your existing application. Our API-first approach allows businesses to harness the power of AI to deliver self-service data access and enhanced reporting and analytics capabilities, all within the workflows and digital spaces their users are already in.

We’ve developed flexible widgets like Data Messenger and Dashboards so software developers can easily integrate AutoQL on the front end of their existing tools. All our widgets are open source and customizable.

For businesses who do not have their own software or portal, we also offer an AutoQL app for Microsoft Teams.

8) What does the AutoQL API do?

The AutoQL API is a powerful and secure API that dynamically translates natural language to database query languages. 

Here’s some quick facts about our API:

  • The AutoQL API is organized around REST.
  • Our API has predictable resource-oriented URLs, accepts and returns JSON-encoded request bodies, and uses standard HTTP response codes and verbs.
  • Our API is secured with JWT in conjunction with an API key.

The AutoQL API makes it possible for business users — even (and especially) non-technical users — to access and analyze data in real time by asking questions in their own words, all from the software and web environments they’re already familiar with.

Learn more about what principles guide our API, how to manage API keys, and more in our API Reference or in our Developer Docs.

9) Who can use AutoQL and who is it for?

AutoQL is a horizontal solution that can be leveraged by enterprises, software application providers, systems integrators, and/or service providers. Any business team that is exploring ways to democratize data access, monetize new and approachable data workflows, reduce strain on internal resources, or differentiate their offerings from competitors can benefit and achieve high ROI by investing in AutoQL.

Click here for more information about how AutoQL can serve your software or industry vertical.

10) Can I access databases in any query language?

We’ve developed AutoQL implementations to support all flavours of SQL (including Traditional Relational Databases and Cloud Data Warehouses such as Big Query, Redshift, and Snowflake). We have also completed successful Proof of Concept implementations with both MongoQL and Cypher. If you’re curious about whether or not AutoQL can be implemented to support another query language, get in touch with our team and we will be more than happy to discuss your options with you.

11) How can I access the AutoQL Portal?

The AutoQL Integrator Portal can be accessed here.

12) What mobile devices does AutoQL work with?

AutoQL is a flexible API-first solution that can be made accessible to end users through our suite of widgets which includes mobile widgets. This means AutoQL works on mobile devices, allowing business teams and users to access their data on demand from anywhere at any time. For developers, check out our Developer Docs to learn more about how you can support an excellent mobile experience on both Android and iOS devices by leveraging our open source widgets.

Getting Started


1) I'm interested in learning more about AutoQL. How do I get started?

Our dedicated team of experts will work closely with you to guide you through each stage of your AutoQL integration, from early stage consulting and discovery, to customizing our AI for your database, planning your feature release, and providing ongoing strategic support.

Reach out to us at info@chata.ai or book a discovery call with a member of our team.

2) What kinds of businesses can benefit from AutoQL?

AutoQL is a must-have solution for any business looking to streamline data-driven workflows, reduce strain on technical resources, enhance existing BI and reporting processes, and/or empower non-technical users (or employees) to access data more easily and intuitively.

3) Do you offer a Proof of Concept for AutoQL?

Yes. We offer a no-cost, no-commitment Proof of Concept opportunity to the companies we work with.

Because every database is unique, all implementations of AutoQL require a completely customized language model. This enables robust coverage of enterprise-grade databases, ensuring that users of all types will be able to ask simple-complex queries and use intuitive, familiar language to surface the data they care about.

During the POC stage, your custom language model will be trained to provide coverage of a specific, mutually agreed-upon use case. This allows you to see and experience how AutoQL works in the context of your own database.

Get in touch with our team to learn more about how this works and how to get started.

4) What regions and languages does AutoQL support?

AutoQL is built to support multi-lingual use cases. We currently have commercial implementations in both English and Latin American Spanish. Connect with us if you’re looking to learn about implementing AutoQL in another language. Our team will be happy to discuss your use case and see if there is a fit!

5) Is AutoQL an on-premises or cloud solution?

AutoQL is primarily a cloud-based solution; however we can enable AutoQL in on-premise and hybrid environments as long as there is a Kubernetes cluster available. Alternatively, AutoQL can also be fully-deployed within your cloud infrastructure. If you’re interested in learning more, get in touch with our team to discuss our flexible deployment and implementation options.

6) What architecture requirements are needed for implementing AutoQL?

AutoQL is an extremely flexible API-first solution that can be customized for any business that uses a relational database.

AutoQL works exceptionally well in cloud-native software solutions, where it can be embedded directly in a web-based interface via our open source widgets (which take just 2-3 hours to implement, on average). We can also integrate with on-premise software systems.

AutoQL can also be leveraged by enterprises looking to streamline data-driven workflows and provide greater data accessibility to their employees. We offer a variety of implementation options for enterprises, including an app for Microsoft Teams and a customizable web application.

7) What should I expect once we get started with AutoQL?

Getting started with AutoQL can be broken out into four key stages: connect, train, implement, and go live.

Stage 1 – Connect: We’ll work with you and your team to configure an encrypted, read-only connection between our cloud and your database. Without storing your data, this connection allows us to train a custom model, execute queries, and pass data back to you.

Stage 2 – Train: Next, we get to work generating training data and building a custom language model specific to your database.

Stage 3 – Implement: Once your custom language model is ready, it’ll be your turn to build and implement a conversational UI in your solution, letting your users query their data from anywhere in your application. At this stage, you can make use of any of our flexible implementation options (all widget components are open source) or opt to build directly on top of our API.

Stage 4 – Go Live: With AutoQL trained on your database and implemented in an interface accessible to your users, you’re ready to start offering conversational access to data on demand to! As users ask questions, their conversational English will be sent up to our cloud and translated into a query language appropriate for your database. Relevant data is then returned to them in easy-to-understand visualizations, all within seconds.

8) How long does it takes to deploy AutoQL?

We have the ability to build, train, and deploy models very quickly. End-to-end implementation and deployment timelines vary, and this is largely dependent on which deployment options you decide to pursue. With all applicable permissions in place and commitments aligned between parties, custom models can be built and deployed to production in just weeks.

9) How long does training take for AutoQL?

Model training time for AutoQL is typically measured in hours, and depends on the size of the training corpus.

10) Can I see a demo of AutoQL?

Looking to book a live demo or chat with a specialist on our team? Visit our website to book a call or send us an email at info@chata.ai and we’ll get back to you shortly.

How AutoQL Works


1) What does ''data on demand'' mean?

We’ve built a suite of proprietary conversational AI technologies that enable the real-time translation of natural language to database query languages. This means that users can ask questions in their own words to query and analyze their data in real time. By making this technology available through our API, businesses can leverage this “data on demand” functionality to democratize access to data in their own solutions and across their organizations.

2) What does ''dynamically translating natural language to SQL'' mean?

When it comes to accessing information from a business’ relational database, team members are typically required to write and run database query language statements (DBQL) like SQL. But this is a time-consuming task that requires the expertise of technically-savvy and database-literate team members.

With AutoQL, any user can simply ask questions in their own words to access and analyze their data.

Through our API, AutoQL receives, understands, and interprets natural language queries, dynamically generates a corresponding database query language statement, executes the DBQL statement against the database through a read-only connection, and returns relevant data to the end user within seconds.

3) How does AutoQL answer questions about my unique database from my unique users?

Each AutoQL integration begins with our team generating custom training data and building a custom language model unique to your database. We handle all the heavy-lifting here, and thanks to the technologies we’ve developed, these processes happen rapidly and with high-precision.

Once we’ve built a training corpus and trained a custom model for your database, AutoQL can be implemented in your solution, allowing your users to ask questions about their data in natural language and instantly receive answers.

4) Does AutoQL work on mobile?

Yes, AutoQL works on mobile devices, allowing business teams and users to access their data on demand from anywhere at any time.

For developers, check out our Developer Docs to learn more about how you can support an excellent mobile experience by leveraging our open source widgets.

5) Do you have a self-service model for AutoQL?

Not quite yet, but this is coming soon. If you are interested in being part of our Beta user group of DIY AutoQL, please contact us to let us know!

6) Does my data need to be in the cloud?

AutoQL is primarily a cloud-based solution; however we can enable AutoQL in on-premise and hybrid environments as long as there is a Kubernetes cluster available. Alternatively, AutoQL can also be fully-deployed within your cloud infrastructure.

Your data remains located wherever you are currently storing it. We do not need to replicate data on our side in order for our solutions to be implemented.

If you’re interested in learning more, get in touch with our team to discuss our flexible deployment and implementation options.

7) Does my data need to be normalized?

Normalizing data can mean a lot of different things, so if you have concerns about whether or not AutoQL will be a good-fit, we recommend booking a call to talk with one of our specialists.

Our general rule of thumb is this: garbage in means garbage out. We can absolutely work with really difficult data sets, but if there are inconsistencies in your data, then you can expect those same inconsistencies to be reflected in the answers users will receive to their queries.

Querying 101


1) How do I know what queries I can ask in AutoQL?

The core value of AutoQL is accessing data easily and intuitively using natural language, or more simply, the words you use every day.

Think about the way you would ask a coworker a data-related question, like: “What was our click-through rate on our newsletter last month?” or “Which sales rep brought in the most new business this quarter?”. Approach querying with AutoQL the same way! Simply type questions in your own words and you’ll receive data responses in just seconds.

Tip: Be clear and succinct. Remember, if your question wouldn’t make sense to another person, you might be missing important context that AutoQL will need in order to answer your question accurately. For example, if you went up to a coworker and said “Expenses”, they’d probably say, “Well, what about expenses?”. But if you went up to that coworker and asked, “What were our total expenses last month compared to this month last year?”, they’d be much more equipped to provide an answer to you.

2) Can the SQL statement that is generated through a user query join multiple tables in a database?

Yes, AutoQL automatically generates table-joining SQL when a user query requires it.

The system is built to dynamically translate natural language into accurate SQL statements that can include multi-table joins, back joins, and alias joins.

3) Is it possible to query across different data sources with AutoQL?

At this time, users can only query one data source. AutoQL can be integrated with a data warehouse or a data lake that brings data from multiple sources together.

4) How does AutoQL handle similar column, table, or item labels in the database?

A key feature of AutoQL’s technology is the ability to disambiguate unique labels. This means the system is trained to determine what a user is referring to, even when that meaning is not explicit.

For example, referencing an “invoice” might mean different things for users in the accounting department vs. users in the warehouse.

Unique labels are taken into account during the integration and training processes, and we’ve built in an intelligent machine learning model that is trained to disambiguate value labels based on the context of the question being asked.

5) Do queries ever fail to return data? What happens if a query doesn’t work?

There are cases where a natural language query may be asked and AutoQL will not immediately return a data response. There’s a handful of reasons why this may occur, but even when a data response cannot be returned immediately, AutoQL will always return a message that provides information about why the query could not be answered, or a prompt to help the user clarify what they are asking.

Here’s a summary of common circumstances that can inhibit a data response from being returned:

  • User Permissions Lacking: If a user attempts to query information that they do not have access to in the database, they will receive an error message indicating that their query could not be executed due to a permissions issue.
  • Confidence Threshold Issue: AutoQL is designed to ensure that only correct data responses are returned in response to user queries. Therefore, AutoQL will not return data if the system is not confident that an optimal SQL statement has been generated.
  • Ambiguous Input or User Error: When a natural language query is received but is not immediately understood by the system, AutoQL has built-in models that act as “safety nets” or “check points”. In such cases, these models kick in to try to determine exactly what data the user is asking for. If this verification step is unsuccessful (whether that be because the meaning of the user’s query is still unclear, or because the data the user wants is not actually present in the database), AutoQL will not return a data response.

Implementation Options


1) What front end implementation options are available for AutoQL?

Once we’ve set up a data source connection and built a custom machine learning model specific to your database, it’ll be your turn to build a custom conversational user interface (CUI) that will serve as a natural language interface to your database. We’ve developed flexible front end widgets to make this process seamless and simple for developers.

Implementation options include Data Messenger and natural language-driven Dashboards, both of which can be directly embedded within an existing front end interface. Developers are welcome to customize and use our widgets however they like — all components are MIT licensed and open source. We currently offer these as React WidgetsVanilla JS WidgetsiOS Components, and Android Components

Tip: Integrations with webbased services are ideal, but our widgets will also run in an Electron wrapper or similar technology for use in desktop applications. We provide hooks so the components can be easily called from buttons or events. 

2) Do I need to use the front end implementation options that are provided? Or can I build directly on top of the API?

There’s no obligation to leverage the widgets we’ve provided. You’re more than welcome to build freely on top of our API to implement AutoQL’s functionality however you like in your own front-end interface.

3) We're an enterprise company. How will implementing AutoQL work for us?

In addition to our open source widgets, we also offer additional implementation options that tend to suit the needs of most enterprises, including our app for Microsoft Teams as well as a lightweight web application that be adapted and implemented for your business.

Get in touch with our team to learn more about these options.

4) Do you offer mobile-friendly widgets?

Yes. We’ve made our Data Messenger widget available for both Android and iOS so you can support seamless mobile experiences for you or your users.

5) Tell me more about AutoQL's Data Messenger

Data Messenger is an embeddable and totally customizable conversational user interface (CUI) designed to facilitate data query and analysis through natural language.

Data Messenger is:

  • Fast and simple to implement (see our Developer Docs for details about how to get set up)
  • Highly flexible and customizable (all components are open source)
  • Easy to use and accessible for all types of users

Learn more about Data Messenger in this short 3-minute demo video.

6) Tell me more about AutoQL's natural language-driven Dashboards

Dashboards are a completely customizable frontend implementation option that allows you to deliver powerful reporting functionality and interactive data visualizations within your software application.

Dashboards employ the foundational natural language to database query language translation technology behind AutoQL and flexible frontend components so software vendors can embed reporting functionality however they want, within any part of their app interface.

AutoQL Dashboards are:

  • Fast and simple to implement (see our Developer Docs for details about how to get set up)
  • Highly flexible and customizable (all components are open source)
  • Easy to use and accessible for all types of users

Learn more about Dashboards in this short 3-minute demo video.

7) How long does it take to implement AutoQL's Data Messenger?

Average implementation time is just 2 hours.

Completely customizable frontend components allow developers to seamlessly embed and brand Data Messenger within an existing application, thereby enabling users to connect instantly and intuitively with their data, simply by asking questions in natural language.

For step-by-step instructions on implementing Data Messenger, start by selecting your preferred widget library:

8) How long does it take to implement AutoQL's Dashboards?

Average implementation time is just 3-4 hours.

Completely customizable frontend components allow developers to seamlessly embed and brand Dashboards within an existing application, thereby making it possible for users to set up and manage Dashboards using natural language so they can easily keep a pulse on the data they care about.

For step-by-step instructions on how to implement Dashboards, start by selecting your preferred widget library:

Partner Ecosystem


 

1) Do you have a Partner program?

We sure do! We work with innovative systems integrators, professional services providers, and technology partners to reimagine and transform the future of data accessibility across every industry.

Get in touch with our team to learn more about the benefits of working with us and how to join our network of innovative partners.

2) What is your Partner Program?

At Chata, we partner with a wide range of companies including Systems Integrators, Professional Services Providers, and Technology Partners. Through our Partner Program, we support referral, co-sell, and white-labelling options. Visit our Partner page to learn more or submit an application to join our partner network!

3) What are the benefits of partnering with Chata?

Data-powered businesses demand innovation & impact. Chata’s Partners make it happen. Here’s a snapshot of some of the key benefits that come with joining our network of partners:

  • Establish your team as innovation trailblazers by introducing the world’s first conversational AI solution for data access to your tech stack.
  • Open the door to delivering custom AI solutions that scale, allowing you to earn credibility and loyalty as you propel businesses toward the data-powered future of tomorrow.
  • Expand current business, attract new customers, and capitalize on recurring revenue-generating activities.
  • Stand out and surpass competitors with AI that offers real business value.
  • Earn referral revenue and leverage shared informational resources so you and your customers realize value and see high ROI, fast.

Read more on our Partners page.

4) How do we become a Partner?

Start by submitting an application to join our partner network. We’ll be in touch to set up an introductory call where we’ll learn about your team and objectives, and share further details about working with us. From there, we’ll establish mutual expectations and outline next steps so we can begin working on shared initiatives that drive value for both companies.

You can learn more about the benefits of partnering with us and how to get involved on the Partners page of our website.

5) Who are Chata's Partners?

At Chata, we partner with a wide range of companies including Systems Integrators, Professional Services Providers, and Technology Partners, offering referral, co-sell, and white-labelling options. Some of our partners include Microsoft, Google Cloud, Snowflake, Insight, Reliable Software, Henson Group, and Bridgewater Labs.

Visit our Partner page to learn more about working with us.

6) Do you work with Systems Integrators, Managed Service Providers, and/or Resellers?

We sure do! We work with innovative systems integrators, professional services providers, and technology partners to reimagine and transform the future of data accessibility across every industry.

Get in touch with our team to learn more about the benefits of working with us and how to join our network of innovative partners.

7) Are there reselling opportunities available?

At Chata, we partner with a wide range of companies including Systems Integrators, Professional Services Providers, and Technology Partners. Through our Partner Program, we support referral, co-sell, and white-labelling options.

Visit our Partner page to learn more about working with us.

AutoQL Pricing


1) Do you offer a free trial for AutoQL?

Every database is unique and we build a custom language model for each customer we work with. This allows us to provide robust coverage for querying enterprise-grade databases, but this also means we’re not able to offer free trials of AutoQL, since there’s no “out of the box” version.

We do, however, offer a no-cost, no-commitment Proof of Concept. This means we won’t take your payment information or charge any up-front fees until value has been proven and you agree to move forward in the process of going to market with AutoQL.

Get in touch with our team to learn more about how this works and how to get started.

2) How does AutoQL's pricing work?

We offer two pricing models: Pay-As-You-Go and Subscription-Based pricing. In both cases, AutoQL pricing is consumption-based (per API call) and works on a sliding scale.

3) What are the benefits of offering a consumption-based pricing model?

We’ve carefully built out our pricing models to optimize benefits for our customers and for the partners we work with.

Here’s some of the core benefits of a consumption-based pricing model:

  • Allows for full transparency and no surprises.
  • No POC fees and no implementation fees derisks the go-to-market process for our Integrators. Billing is only initiated when AutoQL is implemented and being used.
  • Integrators retain control of how they roll out AutoQL – whether that be gradually to a beta group of users, OR to all users in a dedicated new release. 

4) How can I learn more about AutoQL's pricing?

Book a call with our team to learn more about both of our pricing models, how they work, and what the best option is for your business.

5) Where can I buy AutoQL?

If you are interesting in purchasing AutoQL, please contact our team to discuss the options that best suit your needs. We look forward to working with you.

6) Do you charge installation fees?

Nope! We do not charge installation fees.

If you are interesting in getting started with AutoQL, please contact our team. We look forward to working with you.

Privacy & Security


1) Where can I learn more about Chata's approach to privacy and security?

AutoQL is a cloud-based API, so the system itself is hosted securely on our cloud platform. The system communicates between your users and your database, but we do not store a copy of your database in the cloud or keep any of your end users’ information such as login credentials. 

AutoQL can also be integrated with on-premise software solutions.

2) What data access does Chata require from Integrators for implementing AutoQL?

AutoQL is built on the structure of the data storage layer. As such, Chata needs access to the raw data in the storage layer without any other software or API in between in order to facilitate a successful integration.

We’re happy to provide detailed instructions and helpful tips on providing secure access throughout the integration process. More information can be found in our Developer Docs.

3) Do you store a copy of our database or retain any of the data in it?

We never create or store a copy of your database and data will always remain within your system

The only data we store is the minimum data required for AutoQL to run securely and efficiently in your software application. We refer to this as nominal data, or the unique data we identify in your database that your users will ask questions about. This allows us to ensure that queries run quickly and return the results that users are expecting.

For example, a user might ask “How many of each item did Jane Doe buy last month?” In the context of this query, we only store the information that the customer “Jane Doe” exists in that user’s database so an optimal database query can be generated and executed dynamically.

We also store user queries (the questions your users ask in natural language), and we expose this to Integrators in the Integrator Portal. This allows us to provide a direct line of visibility into what users are asking; a feature that offers Integrators critical insight into what their users care about and how they’re using the system.

4) How and when is data encrypted?

Data is encrypted at rest and in flight and we use non-numeric IDs to ensure that data is secure at every level. We use JWT to secure who has access to our system, and for how long. 

Learn more about our security best practices and how we use JWT to enable secure access to our API.

5) Are there user-level permissions or role access permissions in place to control access to data?

Integrators can easily set permission levels for users within our Integrator Portal.

If you have in-house permissions structures, we’ll work with you to build a permissions framework that works for you.  

6) Are your security protocols verified and accredited by a third party?

Yes, Chata is SOC 2 Type II compliant. The Service Organization Controls (SOC) 2 Type II report is granted when a company completes a third-party audit that assesses the efficacy of security protocols, procedures, and controls. The examination includes testing and evaluation of the systems and processes we have in place to verify that we’ve demonstrated a reliable commitment to providing ongoing security assurance.

Achieving compliance indicates that Chata meets a standard of excellence recognized across the tech industry.

Read all about our SOC 2 compliance here.

7) Where can I learn more about Chata's approach to privacy and security?

Security is our top priority at Chata. We take several measures to ensure every implementation of our solutions is completely secure.

For more information, find our security documentation here or contact our team to speak with one of our specialists.

Resources & Support


1) Where can I access Developer Resources?

  • Developer Docs can be found here.
  • API Reference Documentation can be found here.
  • The AutoQL Integrator Portal can be accessed here.

2) What is the Integrator Portal?

As developers ourselves, we know it can be frustrating to do one-off tasks in all the APIs we use, so we wanted to simplify these kinds of processes when it came to our own API.

The AutoQL Integrator Portal is a web app designed to help you implement and successfully manage your AutoQL deployment. It contains tools for developers, data for product managers, and serves as a helpful and easy-to-navigate interface that enables you to facilitate many functionalities of the API.

3) What can I do in the Integrator Portal?

The Integrator Portal has a variety of uses including:

1. Simplifying setup

Initial setup is facilitated through a simple step-by-step process, enabling you to quickly and easily connect databases to AutoQL through the Integrator Portal.

2. Streamlining one-off tasks

Configuration can be done through the simplified GUI in the Portal. Since configuration only has to be done once, you can simply set it and forget it.

3. Accessing data and product insights

Use the Portal as a lens to see what your end users are asking and gain a better understanding of your users’ motivations and needs. In the Portal, you have total visibility into common query trends, allowing you to highlight points of friction and see what data is in highest demand.

4. Developer assistance

Access API Keys, history logs, and all sorts of things that help developers gain important insights and get important work done, faster.

4) How can I access the Integrator Portal?

If you already have an account set up, you can access the Integrator Portal here.

If you require login information or are having issues accessing your account, please send us an email here.

5) I forgot my password for AutoQL.

Forgot your password? Click here to access the AutoQL Portal login area and click on the “Don’t remember your password” link below the sign in area. You’ll be prompted to reset you password here.

6) Where can I access additional resources?

Looking for additional resources? See below for links to some of our most-popular resources. If you have questions, don’t hesitate to reach out to us directly. We’re more than happy to help!

Interested in staying in the loop with all-things AutoQL? Sign up to receive updates from our team here at Chata.