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To create, mantain and iterate AI and analytics takes a lot of time on expensive and valuable developers. Focus your developers' workforce into what brings you revenue!

check "In 20 minutes the equivalent to 1 week of a fullstack team"

EEmbcheck Embed AI - Machine learning suites in 20 lines of code

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Frequently Asked Questions

Don't be left in doubt. We know that we are a complex and
new product, any doubt is welcome.

What is a Data Product?

A Data Product is an asset of your company. A Data Product is a PRODUCT. A good Data Product will not put data in the center, but the user. It's not made only for sharing data, but for giving a proper experience, so that the right people can have the right information and insights at hand to make the right decisions. A Data Product helps in using data to improve operations, decision making and the performance of individuals, organizations and society.

What is the difference between AI Apps and Data Apps?

AI Apps are an extension of Data Apps. A web to share data, like Google Analytics, is a Data App. But when that data you are sharing is partially, mostly or totally predictive data coming from AI and Machine Learning algorithms, then we are talking of AI Apps. Shimoku allows you to create AI Apps fast in a few hours thanks to its predictive suites ready to forecast your KPIs so that you can deliver more than historical data without needing software architecture, AI Engineers or Data Scientists.

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Why Data Apps?

Google says that 50% of the companies worldwide want to share data with their clients and providers. Data Apps are needed when you want to share so much data or with so many people that BI tools are no longer enough. You have multiple pages, accounts and so many use cases that you would need an army to handle it manually. In the rising era of data products, data specialists must be free to create their own data apps with simple code without further dependencies. Shimoku allows you to create Data Apps and AI Apps without needing Data Scientists, Backends, Frontends or DevOps.

How is Shimoku helping me?

Creating a Data Product in the form of Data Apps and AI Apps requires large teams of highly experienced professionals. Moreover, the dependences among them are complex and delivery rates are slow and tricky. Gartner says that 85% of AI initiatives fail. Shimoku allows you to build Data Products, in particular Data Apps and AI Apps, in a few hours, so that you reduce the risk to zero: you do it with a single Data Engineer in hours rather than years.

How fast is create a Data App with Shimoku?

During a demo, a customer told us: "you have done in 20 minutes what would take a whole week for our full stack team". With Shimoku, you just need to: take your data, decide who you want to show it to, and some metadata regarding what sort of chart, grid position, page in the App, and boom! Magically done with a single POST request.

How do I create an AI App with Shimoku?

Shimoku already counts on ready-to-use algorithms for: Churn prediction, Predictive Cohort, Next Purchase Prediction, Sales Forecast Prediction and Anomaly Detection. You can activate any of those suites for your data just by sending the training data to our API and activating the AI option. It happens all automatically, and then you can retrieve that data back to your system or connect to other tools (we already connect some of our predictions to email marketing campaign tools such as Hubspot, Mailchimp or Klaviyo). Actionable AI without Data Science, nor MLOps, nor a Data App team. A Data Engineer becomes a God.

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Boost your developers' skills

Some of the main advantages of an AI Saas Analytics Tool:

Success cases

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Frequently Asked Questions

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Create AI & Analytics that you can embed

Boost your developers' skills

Some of the main advantages of an AI Saas Analytics Tool:

Success cases

Do you have any questions?Frequently Asked Questions

Stay connected

SOCIAL MEDIA

Supported by

Marketing & Sales

IT & Data

Custom SOLUTIONS

Company

Resources

Industries

Language

Do you have any questions?
Frequently Asked Questions