If you've ever been interested in Energy Cards, you probably had a question in your mind:
“Okay, but how does this PicFlow intelligence really work behind the scenes?”
Let's explain this without technical jargon and focus on something simple:
how AI understands what you send and transforms it into a digital art that makes sense.
Step 1: You send what you already have
It all starts with the content you already generate daily:
photos (of games, shows, products, behind-the-scenes)
short videos
audios (speech, music, crowd cheering)
texts (captions, testimonials, written speeches)
You send this material to PicFlow via the app.
Step 2: AI interprets the context
PicFlow was built as an AI-native platform with a multi-LLM layer. This means, in practice, that it uses several combined AI models to understand:
what appears in the image (people, environment, action)
what is being said in the audio or video
the tone of the text ( motivational, emotional, technical, artistic)
the type of moment (training, championship final, vernissage, launch, internal event)
This interpretation is what allows Energy Cards to be not just “pretty effects,” but visual representations coherent with the moment experienced.
Step 3: Choice or suggestion of styles
From this understanding, PicFlow cross-references the context with visual styles that can originate from:
artistic movements (surrealism, pop art, minimalism, glitch, futurism)
cultural scenes (street, sports, urban, cyber, classic)
authorial filters, created in collaboration with artists and designers
You can:
directly choose the style
or let PicFlow suggest approaches that match the content
Step 4: Generation of Energy Cards
With context + style defined, AI generates Energy Cards that:
highlight key elements of the scene (person, action, symbol, environment)
reinforce the emotion of the moment (intensity, calm, celebration, suspense)
maintain an aesthetic line that can be repeated in collections
The focus is not to produce an isolated image, but a card that tells part of the story.
Step 5: Organization into collections
PicFlow allows organizing Energy Cards into collections by:
event or game
tour or season
brand campaign
community or fan club
This facilitates:
revisiting important moments
showing to sponsors, fans, or clients
creating narratives over time
Why multi-LLM matters in practice?
You don't need to understand the technical part, but it's useful to know the impact:
more interpretation accuracy: each model is good at a type of task (image, text, audio…)
more creative flexibility: the platform continuously learns new contexts and styles
more personalization: different profiles (athlete, artist, brand, creator) can have distinct AI behaviors
In the end, the goal is simple:
PicFlow needs to understand you and your context so that each Energy Card looks custom-made.
What this means for the curious
If you're already interested in Energy Cards, understanding this logic helps you see PicFlow not as a “filter app,” but as a visual intelligence infrastructure.
You send what you experience in the physical.
AI interprets.
Energy Cards return this in the form of a visual narrative.
The next step is to experience this intelligence with your own content.