AI: from challenge to innovation
Discover how AI makes your organization more efficient, safer, and more agile.
AI: from challenge to innovation
Discover how AI makes your organization more efficient, safer, and more agile.
What is AI (Artificial Intelligence) and why now?
Artificial Intelligence (AI) makes it possible to analyze large amounts of data, recognize patterns, and make autonomous decisions. From smart assistants to generative models: AI offers unprecedented opportunities for automation, customer interaction, and operational savings.
What is AI (Artificial Intelligence) and why now?
Artificial Intelligence (AI) makes it possible to analyze large amounts of data, recognize patterns, and make autonomous decisions. From smart assistants to generative models: AI offers unprecedented opportunities for automation, customer interaction, and operational savings.
What is AI (Artificial Intelligence) and why now?
Artificial Intelligence (AI) makes it possible to analyze large amounts of data, recognize patterns, and make autonomous decisions. From smart assistants to generative models: AI offers unprecedented opportunities for automation, customer interaction, and operational savings.
Trusted by international clients
Trusted by international clients
Trusted by international clients
Virtual Assistants
Create your own agents for both internal and external use with Copilot Studio. By using Generative AI and Large Language Models (LLM), you can get an answer to all your questions in no time.
Create your own agents for both internal and external use with Copilot Studio. By using Generative AI and Large Language Models (LLM), you can get an answer to all your questions in no time.
Document recognition
Use AI to read and process documents. By labeling documents such as invoices, AI can recognize and process them on its own. This means you no longer have to process them manually. This saves time, money, and is less prone to errors.
Use AI to read and process documents. By labeling documents such as invoices, AI can recognize and process them on its own. This means you no longer have to process them manually. This saves time, money, and is less prone to errors.
Machine Learning
Make use of Machine Learning to make predictions based on historical data alongside data analysis. Thanks to advanced algorithms and self-learning models, your organization becomes increasingly smarter and more efficient.
Make use of Machine Learning to make predictions based on historical data alongside data analysis. Thanks to advanced algorithms and self-learning models, your organization becomes increasingly smarter and more efficient.
Virtual Assistants with Generative AI and Copilot Studio
Nowadays, chatbots are indispensable in the communication between customers and employees. Virtual assistants provide the ability to quickly answer questions and offer solutions. With the use of Generative AI and powerful Large Language Models (LLM) like GPT variants, these assistants can not only handle standard questions but also engage in complex, context-sensitive dialogues.
Nowadays, chatbots are indispensable in the communication between customers and employees. Virtual assistants provide the ability to quickly answer questions and offer solutions. With the use of Generative AI and powerful Large Language Models (LLM) like GPT variants, these assistants can not only handle standard questions but also engage in complex, context-sensitive dialogues.
Deployable internally & externally
Virtual assistants operate on both your public website and within your internal systems (for example, Microsoft Teams or Slack). This way, you can serve customers 24/7 and provide employees with quick access to company information, process instructions, or HR questions.
Virtual assistants operate on both your public website and within your internal systems (for example, Microsoft Teams or Slack). This way, you can serve customers 24/7 and provide employees with quick access to company information, process instructions, or HR questions.
Agents & Chatbots
Behind the scenes, advanced agents are at work: autonomous software entities that take on tasks, initiate workflows, and retrieve data from back-office systems. They respond to natural language, recognize intents, and escalate to a human employee when necessary. This way, assistants can gain access to your existing SharePoint environment, where you have stored documentation of processes in various formats. This gives the assistant access to information about your business processes, allowing it to answer questions as accurately as possible.
Behind the scenes, advanced agents are at work: autonomous software entities that take on tasks, initiate workflows, and retrieve data from back-office systems. They respond to natural language, recognize intents, and escalate to a human employee when necessary. This way, assistants can gain access to your existing SharePoint environment, where you have stored documentation of processes in various formats. This gives the assistant access to information about your business processes, allowing it to answer questions as accurately as possible.
Copilot Studio
With Copilot Studio, you can easily build and manage your own AI agents. This Microsoft tool provides a ready-made framework to train agents on your business data, set custom prompts, and enforce security and compliance rules. This way, you quickly create a virtual assistant that reflects the tone of voice of your organization. Business data, prompts, and other sensitive information remain safe within your own Microsoft environment and are not used to train AI models. For more information on security and data governance, you can consult the Microsoft website here .
With Copilot Studio, you can easily build and manage your own AI agents. This Microsoft tool provides a ready-made framework to train agents on your business data, set custom prompts, and enforce security and compliance rules. This way, you quickly create a virtual assistant that reflects the tone of voice of your organization. Business data, prompts, and other sensitive information remain safe within your own Microsoft environment and are not used to train AI models. For more information on security and data governance, you can consult the Microsoft website here .
Document recognition with AI: efficient, accurate, and cost-saving
Many organizations struggle with the manual processing of purchase invoices, contracts, and other important documents. This is error-prone, time-consuming, and costly: employees spend hours on data entry, checking, and archiving.
Many organizations struggle with the manual processing of purchase invoices, contracts, and other important documents. This is error-prone, time-consuming, and costly: employees spend hours on data entry, checking, and archiving.
Automatic reading and processing
Thanks to OCR (Optical Character Recognition) and smart AI models, invoice data such as supplier, invoice number, date, and amounts are extracted from various file formats. The structured data is then directly forwarded to your ERP or accounting system.
Thanks to OCR (Optical Character Recognition) and smart AI models, invoice data such as supplier, invoice number, date, and amounts are extracted from various file formats. The structured data is then directly forwarded to your ERP or accounting system.
Concrete savings
By automating this workflow, you eliminate manual tasks and minimize the risk of human error. On average, this translates into savings equivalent to a full workday: over 20% time savings for your finance team.
By automating this workflow, you eliminate manual tasks and minimize the risk of human error. On average, this translates into savings equivalent to a full workday: over 20% time savings for your finance team.
Solution: AI-driven document processing
Step 1: Automatic mailbox reading
An AI agent retrieves new invoices from the central email inbox and classifies them by type and supplier.
Step 2: Document recognition (OCR + NLP)
Using Optical Character Recognition (OCR) and Natural Language Processing (NLP), the system automatically extracts invoice data (date, invoice number, amount, VAT rate).
Step 3: Automatic import into the accounting system
The data is sent via an API directly into your ERP or accounting package, including validation of amounts and checks for duplicate entries.
Step 1: Automatic reading of mailbox
An AI agent retrieves new invoices from the central email inbox and classifies them by type and supplier.
Step 2: Document recognition (OCR + NLP)
Using Optical Character Recognition (OCR) and Natural Language Processing (NLP), the system automatically reads invoice data (date, invoice number, amount, VAT rate).
Step 3: Automatic import into accounting system
The data is directly written to the ERP or accounting software via an API, including validation of amounts and checking for duplicate processing.
Machine Learning: smart models for continuous optimization
Machine Learning (ML) is at the core of data-driven innovation. Instead of using static rules, ML models utilize historical and current data to discover patterns, make predictions, and support decision-making.
Machine Learning (ML) is at the core of data-driven innovation. Instead of using static rules, ML models utilize historical and current data to discover patterns, make predictions, and support decision-making.
Anomaly Detection: detecting deviations early
With anomaly detection, you automatically identify unusual patterns in your data before they lead to problems. By continuously monitoring AI algorithms for deviations, you can intervene immediately and prevent costs or damage.
With anomaly detection, you automatically identify unusual patterns in your data before they lead to problems. By continuously monitoring AI algorithms for deviations, you can intervene immediately and prevent costs or damage.
Demand forecasting: optimal inventory and planning
With demand forecasting, you use machine learning models to make accurate predictions based on historical sales data, seasonal patterns, and external factors. This enables you to proactively align inventories, production schedules, and purchasing strategies with the expected customer demand.
With demand forecasting, you use machine learning models to make accurate predictions based on historical sales data, seasonal patterns, and external factors. This enables you to proactively align inventories, production schedules, and purchasing strategies with the expected customer demand.
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Curious about how you can implement AI within your organization?
Contact us and discover what VDS can mean for your organization in the field of Artificial Intelligence.
Curious about how you can implement AI within your organization?
Contact us and discover what VDS can mean for your organization in the field of Artificial Intelligence.
Curious about how you can implement AI within your organization?
Contact us and discover what VDS can mean for your organization in the field of Artificial Intelligence.