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Productise AI at Scale

At Faktion, we believe AI unlocks true business potential and secures a competitive edge. Our mission is empowering industry winners with AI. We accelerate growth by integrating AI into every aspect of your business.

And how do we achieve this? We collaborate with businesses to conceptualise AI applications, execute solutions, and develop user-friendly interfaces that empower users to monitor, manage, and scale AI without specialised coding skills.

Meet the talented individuals behind our success.

Three Faktion team members sitting on a couch, collaborating with laptops and smiling in a casual office setting.A woman focused on her computer screen, working in a bright office space with green plants in the background.A man in glasses and a dark sweater working intently at a desktop computer in a modern open office.A woman with curly hair and glasses wearing a Faktion sweatshirt, listening attentively during a meeting.A group of six Faktion team members sitting together, smiling and engaging in a casual discussion under rainbow flags.

Intelligent platform for chatbots and voicebots in 100+ languages

An Intelligent Document Processing platform to automate every document and email workflow

Proud of our successful spin-offs

Both platforms have been mentioned in the respective Gartner quadrants. Metamaze has been awarded ‘Tech Start-up of the year 2022 by Datanews’.

This experience is now being fully leveraged to help our clients build the products and capabilities to outcompete within their industries.

Chatlayer empowers smart businesses to have authentic, valuable conversations with their customers - through the power of AI. Chatlayer's clients are global leaders in their fields, using intelligent conversational AI to automate customer engagement, increase quality, drive efficiency, and bring customer intimacy to the next level. Across multiple channels, in 125 languages.

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Screenshot of Chatlayer’s NLP performance dashboard showing intent training metrics. The interface lists various intents with corresponding expression counts, diversity, and misclassifications. A summary on the right highlights the number of intents, low-diversity expressions, and overall model score, which is currently 88 (+3%).Screenshot of Chatlayer’s user flow analytics dashboard for a chatbot. It visualizes the flow of 30,250 user messages across various intents like booking train tickets or reporting lost items. The diagram shows how user queries are distributed and highlights areas where the bot did not understand the intent, including metrics for misunderstood inputs.Screenshot of the Chatlayer.ai platform showing the NLP interface for the Proximus bot. The left panel displays a list of intents such as ‘Book train ticket’ and ‘Who are you’ with usage stats for Dutch, English, and French. The right panel shows sample expressions in Dutch for the selected intent, including highlighted entities like city names and time references.

Metamaze is an enterprise-graded AI-driven Intelligent Document Processing (IDP) SaaS platform that enables companies to automatically process, extract, structure and validate any kind of information from any type of document.

Read full case
Screenshot of the document type management interface in Metamaze. A grid layout shows various document types like “Bank Statement,” “Certificate of Origin,” and “Bill of Lading,” each with metadata on training status, creation date, and owner. Filters and search options are available at the top.Screenshot of Metamaze’s data annotation tool for document understanding. The left section lists extracted entities such as supplier name, VAT, and company addresses. The right section shows the annotated invoice with composite address components (street, postal code, city) highlighted and grouped under the company_address entity.Screenshot of Metamaze’s document validation interface showing an invoice under review. The left pane displays metadata like invoice status, type, and annotations. The right pane previews the invoice document with highlighted fields such as invoice date and VAT. The middle section flags issues like invalid values and missing product data, along with extracted entities and their confidence scores.

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