How to gain value from AI and ML?
Our AI software has a wide range of readily available Machine Learning and Deep Learning features. These always follow the same process: you choose the practical application, set the parameters as desired and the best performing model is generated and automatically proposed.
Automate repetitive operations
Automating tasks provides enormous efficiency gains: just think of the processing of requests and orders or the preparation of quotations. Dilaco ML can be used to structure and analyze incoming information. Tasks that the AI cannot handle itself are automatically passed on to the appropriate processors.
Predictive maintenance
More and more companies are moving away from the traditional approach to machine maintenance, where equipment is always serviced at the same time interval. Data sensors can perfectly map out the effective load on machines. This allows maintenance to be scheduled in a smarter way and irregularities to be accurately predicted. This predictive maintenance in turn reduces machine downtime and limits additional production loss to an absolute minimum.
Predicting lead qualification
Dilaco ML detects patterns in sales data, compiling relevant groups of customers. From this, a predictive model can be generated that assigns new leads to a specific group - for example, based on the actions a lead takes on your website. In this way, you qualify the potential of a lead in a scientific, data-based way. You can then have the qualified leads automatically assigned to the appropriate sales profile.
Collect and analyze sales data for the right action
The right information is crucial to successfully closing deals. Important data is often scattered across various channels, such as CRM systems, spreadsheets, emails and notes. Sellers often don't have all the information at the right time to draw the right conclusions. AI brings together information from different channels, distilling patterns and insights and suggesting actions that increase the likelihood of a sale.
Extensive personalization
Customers expect a personalized experience - even in a B2B context. A generic offer no longer suffices. Use Dilaco ML to personalize content on your website, offer relevant products in your webshop or build smart conversion-enhancing chatbots.
Data-based personas
Defining clear personas or customer groups is crucial in a modern marketing process. After all, you want to provide each target group with the right message. Too often, personas are still drawn up based on subjective criteria, without supporting data. Through clustering, Dilaco ML can define personas in a scientific and data-driven way.
Discover the ideal conversion path
In online marketing you probably have an idea of the cost of a conversion through different channels. But what factors cause one visitor to convert and not another? UX experts and marketers rely on their experience to make suggestions, but they can't possibly map and evaluate each individual visitor action. With AI, they can.
Chatbot
Customers expect instant feedback. Intelligent chatbots can provide first-line support that filters requests. Frequently asked questions are thereby automatically answered by a personalized chatbot. More complex questions are assessed and passed on to a human team member. That automatic triage speeds up the service process and eases workload.
Intelligent support assistant
Experienced support staff can quickly answer complex questions thanks to their experience. However, even the most seasoned employee does not have access to all the information present in an enterprise. With the help of AI, huge amounts of data can be searched and patterns in historical data can be detected. From there, supporting info can be offered to employees or suggestions can be made for the best follow-up action to reach a solution faster.
Control and reporting
Dilaco ML can also be used to check manually executed administrative processes. The machine then looks for irregularities or anomalies that could indicate errors. Once a risk has been detected, it can be subjected to additional checks. This reduces the error rate in your administrative processes.
Process and organize incoming data
Dilaco ML can be enabled as a gatekeeper that screens and assesses large amounts of data for further processing. This greatly reduces the workload. Only a very limited amount of input is still forwarded for human processing. That manual processing will also always be used by the machine as feedback, making the algorithm smarter and smarter and further reducing the amount of manual processing.
The most appropriate profile, with data as a guide
Education level and hard skills can be defined for most jobs. In addition, sometimes there are success factors for a job that you wouldn't have suspected or inferred on your own. Specific interests, hobbies, personal background or even geographical factors that determine a candidate's perfect match with a job opening? With AI, you gain insights from historical data and create the most suitable profile for your open positions.
The best match between profile, job and HR policy
A manual screening of cover letters is a time-consuming and repetitive task, sometimes performed on autopilot. This increases the likelihood that important information in a resume will be overlooked. Use Dilaco ML to make thorough analyses of job openings and candidate profiles. This way you will automatically detect the best matches. After recruitment, you can use the AI engine to monitor the application of your HR policies and regulations.
Automated interactive intake
An initial screening is often done superficially based on a resume. Often, candidates who don't seem to have the right profile right away on paper don't advance to a round of interviews. A chatbot or intelligent quiz can conduct an initial exploratory interview with a candidate, ensuring that any white ravens are not left out.
Classification
Applications for AI and DL are driven by three main variables: data processing, algorithms and parameters of both. Those variables must be combined and evaluated in interaction to achieve accuracy and performance. They determine the quality of the final model for AI and DL.
Those crucial choices and interactions between algorithm, data processing and parameterization - also called hypertuning - are performed completely independently by the Dilaco ML. This speeds up the entire process, from defining an application to delivering a high-performance application for AI and DL.
Clustering
Clustering algorithms can independently group data based on similarities between these groups. These groups or clusters can then be used in Dilaco ML to assign new data to the most relevant group.
An example for which clustering is used is the creation of marketing personas: defining customer groups with similar profiles and needs. But there is more: clustering algorithms are equally well deployed for fraud detection, predictive maintenance and in numerous other domains.
Prediction
Predictive Analytics with Machine learning or Deep Learning can be done in different ways, depending on the underlying algorithm used to build the predictive model. All predictive models aim to predict unknown values, properties or events. Prediction often uses algorithms for classification, clustering, pattern recognition, and image recognition, among others. The following popular types are available by default in Trendskout: forecasting, anomaly prediction and prediction of labels or types.
Image recognition & pattern recognition
Image recognition and pattern recognition is a very specific type of AI and DL with high-dimensional data, such as images. That means that one data point - think of a photo or a video frame - contains a lot of information. For example, the number of pixels in a single photo quickly runs into the millions. Because of the high dimensionality of this kind of data, neural networks are well suited to processing it, whether it's classifying images or recognizing objects or patterns.
Chatbot
Chatbots are supported in Dilaco ML within the Connect - Analyse - Automate flow. In practice, the connect step can be used to link Dilaco ML to the chatbot's digital channel. In this way, the Dilaco ML is used to make your chatbot intelligent and self-learning.
After linking with input, and training data, the user can select in which way the chatbot should be trained. That selection is made based on the availability of training data. If training data is available, Dilaco ML can allow the chatbot to train independently based on that data. If training data is not available, the chatbot can be trained via interaction with the end user.
Recommendation
Recommendations are an integrally supported AI feature on the Dilaco ML platform. A recommendation engine - the system that makes the recommendations - is used to suggest hyper-personalized services, content or products.
Recommendation engines can be supported by different types of classification and clustering algorithms, which are implemented in such a way that they can recommend a particular service or product. This often involves the use of distance functions, where for a given data point (e.g., a visitor on a website), another closest "data point" (e.g., the most relevant blog post) is determined.
Prescriptive Analytics
Many applications for AI, DL and ML focus on predicting a value or event - Predictive Analytics. With Dilaco ML, this application goes one step further than predictions. It also provides a component that prescribes concrete actions (Next Best Action) to achieve certain goals in the most effective way.
A practical example of this is an account manager who gets a suggestion for a next customer action recommended via Dilaco ML, based on his or her goals. Prescriptive analytics, like other AI features, can be deployed in Dilaco ML via the connect-analysis-automate-flow.
Text Classification
Text classification reads and interprets texts for various applications in customer service, administration, sales & marketing and operations.
This interpretation is based on a text classification model that is trained on labeled text data. This is done - as with other classification algorithms - in two phases: a training step and the production phase. In the production phase, the pre-trained model is used to start classifying or labeling new texts. To train that classification model, techniques such as neural networks and NLP (Natural Language Processing) are used.
Impact Analysis
Impact Analysis answers questions like "Why are sales targets for a certain product line not being met?", "Why does a certain type of machine need more maintenance?", "What motivates my employees?" or "What drives my ROI?". This type of analysis looks for the underlying causes of why something happens - or doesn't happen.
For this impact analysis, techniques such as propensity modeling are applied, in combination with the latest Deep Learning technology. This makes it possible to discover all the links and insights in your data and in the processes that drive your organization. This is impossible for a human brain to do in a realistic time frame. Dilaco ML can expose the insights in an automated way, based on the three connect-analysis-automate steps.
Software Development
Finding custom software, unique to your business is a difficult task. That’s why Dilaco helps you further with custom-made business software in order to stay up-to-date and to be able to grow along with the constant evolutions. Dilaco has the expertise in developing custom software for the specific needs of your company.
Application Development
Dilaco specializes in application development or the creation of computer programs for the various tasks within your company. Our applications help to automate your business processes and increase business efficiency.
Front-end & back-end development
Our Front-End Developers take care of the unique experience of your company and make sure that your application is part of your identity. Back-End Developers, on the other hand, are the backstage of your successful application. They work on the quality and sustainability of your applications through digital architecture and problem-solving thinking.
Web Development
A decisive website or an online platform are the basis for digital success. Dilaco ensures that your online platforms work quickly and get a responsive web design for all screens. This is about a balance between graphic design and ease of use.
Mobile Development
The digital age foresees not only an evolution in technologies, but also in devices. Think, for example, of the smartphone with a smart watch. Mobile devices are now firmly in our hands thanks to the enormous range of apps on offer. As a company it is important to be present with your customers and employees and to build a unique and simple user experience. Our Dilaco designers offer mobile developments for all platforms relevant to your business.