Reusable AI: Raise the treasure — Part 3

AI use cases show great diversity. Not every business problem a priori has an unknown so­lu­tion and requires research and scientific work. Many companies have similar problems, and these can be sol­ved with reusable AI applications. AI can be like cooking.

In our previous article, we looked into the survey results of renowned analysts with respect to AI in business. Their findings can be viewed as top-level features of a future AI business plat­form:

• Reusable ingredients for AI solutions
• AI recipes for rapid response to recurring and similar problems
• Fast implementation through code-free orchestration
• “Predict as you train” paradigm for seamless operationalization
• Case management for a 360° view on AI solutions
• AI white boxing with comprehensible recipes to install trust
• Rapid solution deployment through dual use platforms

In this article, we introduce a next-generation AI business platform that implements these fea­tures right now: PredictiveWorks.

PredictiveWorks. is an AI catalyst and business-ready AI working horse with the mission to es­tablish reusable AI. The focus is to boost small DataOps teams with code-free and reusable AI recipes for a wide variety of business use cases.

What fast.ai claims for deep learning, “making neural nets uncool again”, is our claim for the full spectrum of machine intelligence: We want to make machine intelligence as accessible as possible for business teams in companies who are not listed as Fortune 500s.

Seamless integration

Before we continue to discuss PredictiveWorks. in more detail, we want to point out (again) that data processing is organized as a structured process, and AI is an important contributor to this process:

A standard data process comprises the phases: track, collect, aggregate, analyze, optimize and action.

AI is key to reach the action phase, but it is definitely not made to cover all phases of the en­tire data process. An important, but often neglected consequence: Corporate AI adoption must be part of a data strategy, and AI platforms complement plat­forms that track, col­lect and aggregate data.

Suppose a small or midsize manufacturer aims to optimize resource consumption or predict the next best maintenance interval:

Trying to directly connect an AI platform to a variety of sensors to compute insights from noi­sy raw data and ignoring that great IoT platforms are made for just this task, reveals a missing data stra­te­gy. With an expensive but avoidable effort to reinvent the wheel again and again. This argument holds for most of AI’s business use cases and shifts the focus from raw data to seamlessly connecting to appropriate data platforms that create the basis for AI applications.

PredictiveWorks. complements Google CDAP’s built-in data connectors for a wide variety of po­pular cloud services by 50+ purpose-built connectors from Cyber Defense and Internet-of-Things to E-Com­merce and Marketing platforms.

End-to-end recipes

Business-ready AI platforms must not restrict to the machine intelligence level. It is important that they provide an end-to-end support from business prob­lem to associated tasks and down to AI workflows.

PredictiveWorks. connects dynamic case and AI work­flow ma­na­gement with a 4-level AI tax­o­no­­my: AI projects receive a structured semantic guidance and every AI solution is trans­form­ed in­to a 4-layer bu­siness ob­ject — machine readable and human understandable.

It is an all-in-one configurable informa­tion package that describes the entire architecture of an AI solution, from business case down to machine readable instructions for a code gene­ra­tor to build executable AI workflows with a click. At any time, business users find answers why a certain data connector and operator has been selected, how they fit to a certain project task and what all of this has to do with the origi­na­ting problem. Because of their configurable nature, these business objects represent and are named AI so­lu­tion templates.

Next, we give a brief overview of PredictiveWorks.’ AI taxonomy.

Cases

The first taxonomy level is represented by a business case. Cases, adopted from dynamic case manage­ment, record the high-level business context:

The specific reason for the AI solution, why the specific approach is important for the project and more. Business cases prepare the basis to reuse projects for similar problems, accelerate the onboar­ding process of re­cently hired employees and more.

Tasks

The second level is defined by business tasks to organize busi­ness cases into more detailed tasks. Business tasks can be categorized along proven phases of analytics pro­cesses: It is the CRoss- Indus­try- Stan­dard- Process for Data Mi­­ning on the one hand and the Analy­tics Solu­tions Uni­fied Me­thods for Data M i­ning & Pre­dictive Analytics on the other hand.

We support five phases: Understand, Prepare, Build, Evaluate & Ope­rate. Sol­ving a business prob­­lem usually starts top down and with tasks to understand the problem and derive ideas how to solve it.

Blueprints

The third taxonomy level is defined by blueprints. A blueprint defines the logical plan of an AI application and determines which components are needed, how they interact and how they have to be confi­gu­red to turn low value data into high value insights.

Blueprints are categorized by two semantic dimensions:

• Analytics. Descriptive, Diag­nostic, Declarative, Predictive and Prescriptive
• Purpose. Discover, In­gest, Learn and Predict.

Plugins

Instead of writing software to implement AI applications the traditional way, Pre­dic­tive­Works. abstracts from software engineering and shifts the focus to application design.

More than 200 pre-built & reusable Lego-like building blocks (plugins) exist, that can be configured and plugged together with a point-and-click data workflow designer to specify logical plans (blueprints). An application generator then turns every blue­print into an exe­cutable AI application. Plugins define the fourth level of PredictiveWorks. AI taxonomy. They can be categorized as Source or Sink of a data workflow, as Action, Alert, Analytics, Condition, Lookup & Trans­form.

The image illustrates how PredictiveWorks. exposes the DNA of a botnet detection solu­tion in terms of business case, tasks, blueprints and pre-built plugins. Comprehensible and re­usa­ble business knowledge.

Template Hub

PredictiveWorks. responds to every business problem with a structured AI solution template organized along a 4-layer architecture. It is an important simplification for business:

Instead of managing hundreds of platforms and services, a single platform with a single tech­nology, learning curve and user experience remains to be operated for many different use cases.

So, AI solution templates move into the spotlight as the next real business assets when it comes to transform every business process into a data-centric process. They can be registered and made available in a knowledge hub, sent by email or otherwise distributed. Easy access to best practice AI recipes is an important step to facilitate AI adoption. AI temp­lates, however, do more: They describe, explain and expose — from problem down to AI work­flows — every stage of an AI solution.

So, business users understand what their solutions do with their data — step by step. It is the opposite of magic black boxes, installs trust and further increases acceptance in business to use AI for human decision making.

PredictiveWorks. provides a template (knowledge) hub for a wide variety of reusable business cases, co­vering Cyber Defense, Internet of Things, E-Commerce and Marketing. This hub integrates a template recommendation and search engine and ships with all ingre­di­ents to offer the widely accepted user experience of a marketplace.

Boost AI Projects

Accelerating AI projects and relying on a resilient business process are key to reach millions of smaller companies. The implementation of the magic formula “enable few to reach mil­lions” defines Pre­dic­tive­Works.’ traction and contributes to a sustainable democratization of AI.

AI projects will be organized along the following process and trigger the future AI wave:

1. Understand Problem

Knowing the business problem, its symptoms, drivers, potential risks and also desired outcome defines the starting point for any solution strategy, and it is often this initial step that slows down AI projects from the very beginning.

PredictiveWorks. template hub is organized as a marketplace with smart search and recom­men­dation support, to help users get inspired by potentially similar symptoms, drivers and more. So, tedious and lengthy meetings are avoided, and AI projects gain traction from the beginning as they start with the evaluation of a set of matching AI solution templates.

2. Select Template

AI recipes provide a 360° end-to-end view, from business problem down to appropriate work­flows for training AI models and computing insights. This problem-to-solution white boxing en­ables solution providers and their customers to select the right template for the right problem fast.

3. Customize Template

Many SMEs face similar problems, but they are certainly not identical. You might need to add an extra business task and data sources as well as destinations may slightly differ. There also can be a need to add different data operators to cover other business rules.

PredictiveWorks. offers customization and orchestration of every AI solution template from mo­­difying business case to business tasks and AI workflows without the need to write any line of code. This enables solution providers to thrill their customers project with a rapid approach right from the beginning.

4. Register Template

PredictiveWorks.’ mission is to make AI solutions reusable. On the one hand, this reflects the fact that not every business problem is unique and accompanied by an unknown solution that needs research and scientific work. On the other hand, it is the only meaningful strategy to re­duce the size of expert teams and accelerate projects to minimize time to value for mil­lions of smaller companies.

So, PredictiveWorks. registers every created or updated AI solution template in its template hub by default to ensure reusability and sharing across project and even business boundaries.

5. Generate Solution

AI solution templates represent best practice AI recipes and are important business assets to sig­nificantly accelerate AI projects. Templates are human understandable and machine read­able. The latter means that they contain machine readable instructions to automatically turn AI workflows into executable software binaries — with PredictiveWorks. integrated code gene­rator.

PredictiveWorks. was made to support solution providers with an AI working horse to respond to their customer needs fast. To finally reach this goal and have a customized AI solution avail­able, a single step is left:

AI solution providers leverage the executable binaries of the high-level training workflow to create the respective AI model(s). PredictiveWorks. supports this step with a big data runtime environment to exe­cute the train­ing binaries. An integrated model management registers every model, including para­me­ters, version and achieved accuracy.

6. Deploy Solution

PredictiveWorks. supports the “predict as you train” paradigm and guarantees fast opera­tio­na­lization and deployment. Business users will receive the same platform for predictions that was used for training purposes with trained and registered AI models and the executable bi­na­ries for the production workflow.

PredictiveWorks. is designed as a dual-use platform to seamlessly support both phases of AI solutions with the same platform and technology. Deploying AI solutions has never been easier and faster.

Making AI uncool

Todays’ corporate AI adoption is cumbersome. More than 85% of AI projects never make it in­to pro­duction and do not return their investments. Even worse, in Europe alone, more than 1.6 million SMEs wait for AI — a clear indication that there is no momentum in business.

PredictiveWorks. is an AI Catalyst and it is made to change the current AI process. The focus is on so­lu­tion reusability, fast operationalization and deployment.

The key assets are AI solution temp­lates that can be orchestrated and customized without wri­ting a single line of code. Templates provided a structured end-to-end view on AI solutions from business problem down to technical AI workflows that are backed by Lego-like toolkit of 200+ prebuilt data connectors and operators.

It has never been easier for an AI solution provider to respond to customer needs with small DataOps teams and a minimal time-to-value. PredictiveWorks. makes building AI solution like cooking, with the right ingredients, the right recipes to generate the right AI dish for millions of waiting SMEs. Solution providers can perform significantly more AI projects in shorter periods of time.

This implements the magic formula “enable few to reach millions” and creates the missing AI momentum in business.

PredictiveWorks. is the basis for a reliable and structured process to turn business problems into reusable AI solution. That and the integration of main concepts of dynamic case manage­ment make AI projects uncool again. Agile project management methods can be used to plan and control AI projects in a given bud­get and time frame.

AI can be like cooking — ready to open an AI restaurant?

Originally published at https://www.linkedin.com.