AI Analyst Builder enables teams to create custom AI analysts without coding. These analysts answer data questions via a chat interface like ChatGPT. Tailored to specific business processes and data, it ensures accurate results and avoids hallucination.
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Congratulations on the launch of AI Analyst Builder! Could you please clarify if AI Analyst Builder integrates seamlessly with popular PPC platforms like Google Ads and Facebook Ads? What kind of customizations are available to tailor the AI Analyst to meet specific PPC campaign goals and metrics?
@paige4ever Hey Paige - thanks for the question, would you mind telling more about the use case / pain point you want to solve?
Connectors are coming in the very next release, yes.
Re customization - need to know a bit more, but you can define the context and goals for particular scenarios.
Hey @anton_vaisburd
Datrics AI Analyst Builder is a tool that helps you create smart AI helpers without writing any code. These AI helpers can answer your data questions just like you talk to a friend. They are super smart because they know your business inside and out, so they give you correct answers every time. No more guessing or wrong information!
@howl_owl Hey - thanks for the question
* Repeatable scenarios working with multiple data sources, including dynamic
* embeddable into your product, could be run locally/securely without data exposure
* flexibility to onboard and use business logic and vocabulary, e.g. how to calculate LTV, what formulas to use - and then to be shared with business users.
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Datrics AI Analyst Builder is a game-changer for data analytics teams! 🚀 The no-code approach to creating custom AI analysts is perfect for empowering non-technical team members to derive insights quickly and efficiently. The flexibility and ease of use make it a must-have tool for any organization looking to leverage AI for data-driven decision-making. Kudos to the team for this innovative solution!
Congrats on the launch! How do you ensure accuracy of responses? In my experience data is often difficult to analyze without a good understanding of the whole pipeline.
@jack_michalak hey Jack - that’s actually what we solve using our product. So in addition to intelligence layer on top of LLM (Agent logic) that decomposes the task, we give the users possibility to add their own deterministic flows. It could be done in a descriptive way - just telling what steps should be done for particular scenario, or in a way of a low-code interface (basically you easily create an API that is triggered from user interface)
@anton_vaisburd Ah, so you rely on people keeping additional information updated in your tool? I think that makes sense, it's just an additional step that's easy to forget.
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