Creation of AI Agent

Good day!

We can assist with the development of an AI agent for automating the creation of packaging design and product labeling. We have experience with AI solutions, content generation, RAG systems, and the automation of design processes. We can implement:
• generation of new packaging designs based on the brand book and existing layouts;
• creation of packaging series for different flavors and product lines;
• automatic generation of labels for different countries and languages;
• work with PSD, AI, PDF, and other source files;
• preservation of corporate style, colors, fonts, and layout structure;
• preparation of materials for printing according to technical requirements;
… • generation of mockup visualizations, banners, and marketing materials;
• an AI assistant for making edits via text commands.
For implementation, we see it as appropriate to use a combination of LLM, RAG knowledge base (brand book, templates, labeling requirements), generative AI models, and a module for preparing production files. We are ready to discuss current processes, the scope of source materials, and propose the architecture of the solution, timelines, and budget for implementation.

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Hello.
I can develop an AI agent for generating and adapting packaging for sports nutrition.

The solution will be based on a combination of AI + knowledge base of the brand book + template layouts. The agent will be able to create new designs based on text requests, adapt packaging for different flavors and markets, as well as automatically generate labels (composition, nutritional values, warnings, barcodes) considering the requirements of different countries.

It is also possible to implement file preparation for printing and generate versions for marketplaces and advertising.

I am ready to propose an MVP architecture and implementation stages.

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We already have a practically ready similar solution for AI agents for brands, which can be quickly adapted for sports nutrition packaging and launch the first working prototype.

In terms of timelines, I would estimate 6-7 weeks for a version where the agent can work with the brand book, element library, labeling texts, markets, and packaging templates.
For the budget, the starting point is around 185,000 UAH for the first stage with the prototype, file pipeline, and human verification of the result before printing.

Here, it's better to make AI not as a magic button, but as a managed system - the brand book and labeling rules in the knowledge base, a separate layer for generating visuals, a separate layer for checking sizes, bleed, safe zones, and mandatory blocks. This reduces the risk that the agent will create something beautiful but ruin the logo, font, or legally important text.

Note, there’s a nuance - I would leave the final PSD, AI, and PDF for printing with mandatory preview and confirmation from the designer, because printing mistakes are unforgiving =)

… Relevant examples:
- https://business.ingello.com/vorfahr - AI and automation of complex workflows with data, rules, and user scenarios
- https://business.ingello.com/fractal - agent architecture where tasks are broken down into steps and controlled by the system
- https://business.ingello.com/prime-eva - close to retail, visual materials, and scalable product logic

Main page for our systems for the exchange:
- https://systems-fl.ingello.com

I’ll clarify 2 points to avoid guessing on coffee grounds, or rather, on a protein shake:
- What are the main source files currently - PSD, AI, PDF, or are there already templates in Figma?
- Which markets need to be covered in the first stage - Ukraine, EU, Thailand, Japan, or only 1-2 priority countries?

If this is okay, we can start with a short design and prototype phase within the exchange - gather the brand book, 3-5 packaging examples, labeling rules, and demonstrate a working scenario for creating a new flavor.

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Hello! We understand the task and can take on the development of such an AI agent for the sports nutrition brand.

We have experience in AI automation, working with visual generation, content adaptation, and building systems tailored to a specific brand. In this project, it is important not just to "generate images," but to maintain the brand style, packaging structure, labeling logic, and the ability to quickly adapt the design for different markets and product lines.

We are ready to discuss the details, review the brand book, examples of current packaging, and source files. After that, we can propose a clear implementation plan, timelines, and costs.

If necessary, we can work in stages and start with an MVP to first show a working version of the agent on several products/flavors.

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Good day. I am ready to complete this project and have extensive experience in developing various applications.

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It seems you need not just an image generator, but a full-fledged AI packaging designer that can work according to the brand book, maintain brand identity, and automatically adapt packaging for different markets and languages.

I have created AI agents and automated systems based on GPT, Voiceflow, and Make.com that took input data, used knowledge bases, and produced standardized results without manual processing. For your project, I would implement a system with the brand book as a knowledge base, control over brand elements, automatic generation of labels, and a workflow for creating new SKUs based on text requests.

I am particularly interested in the task of automatic localization of packaging for different countries and preparing files for printing while adhering to technical requirements.

Could you please let me know if the brand book, packaging templates, and AI/PSD source files already exist, or do they also need to be structured into a single knowledge base for the agent?

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To automate the design of FitWin sports nutrition, an AI agent is needed that can generate flavor concepts like Pistachio Coconut and layout labels according to EU or Thailand standards. The main challenge is controlling the placement of technical elements, composition, barcodes, and nutritional information without distorting the proportions of the logos and brand fonts.
I have developed similar workflows based on the LLM API for texts and ControlNet for graphics. Python automation scripts are used for precise assembly of PSD/PDF layouts. A rough outline of my approach to label generation:
def applylabel(template, textdata, coords):
canvas = loadpdftemplate(template)
canvas.drawtext(coords['nutrients'], textdata['nutrients'])
canvas.save()
This ensures compliance with printing technical requirements and eliminates distortion of important data.
Please send a link to the brand book and an example layout for FitWin, and I will prepare a concept for the agent's architecture by tomorrow.

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Hello. I work with Next.js/FastAPI. Ready for collaboration.

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Hello!

I’m interested in your project. I work with AI automation, LLM systems, image generation, RAG/knowledge bases, and custom integrations. I have experience with similar workflows for automated content generation, visual assets, product content, and brand-based AI tools.

I see this project not just as an image generator, but as an AI agent connected to a structured brand knowledge base: brand book, logos, fonts, colors, packaging examples, labeling rules, product data, and market/language requirements.

At the MVP stage, the system can allow users to upload brand materials and packaging references, then generate packaging concepts, labeling text blocks, visual directions, and several design variations for new products or flavors.

Later, we can add adaptation of existing layouts for new product names, ingredients, languages, markets, mockups, banners, POS materials, and packaging series for multiple flavors in one consistent style.
…
For final print-ready files like AI/PSD/PDF, I recommend a hybrid approach: AI handles concepts, content, adaptation, and mockups, while final files are created from controlled templates or reviewed by a designer/prepress specialist to ensure correct fonts, colors, logo usage, bleed zones, and labeling accuracy.

I can help build the full solution: architecture, brand knowledge base, AI logic, file-processing workflows, UI, and automation.

I’d be happy to discuss what materials you already have: brand book, packaging examples, PSD/AI/PDF files, languages, and target markets.

Hello, I am a Senior Full-stack developer and AI architect with extensive experience in building AI agents. And I will say right away: we will implement this solution using Hermes 3 (or Hermes 2.5 Pro), as this stack is perfectly suited for such tasks.

🧬 Why Hermes?
The models of the Hermes family (especially finely tuned versions from Nous Research) have two critical advantages for your project:

Benchmark Function Calling: Hermes perfectly transforms a vague user text request ("Make a Pistachio Coconut bar...") into a clear structured JSON. It will flawlessly call image generation functions, substitute the necessary translations, and brand color codes.

Steerability: Hermes will not "fantasize" or change your brand book. It strictly adheres to the given framework (system prompt), ensuring the preservation of original logos, safe zones, and fonts.

… 🛠 Technical architecture of the AI agent
To work with high-resolution graphics, we will create a hybrid system:

Agent core (Orchestrator): Hermes 3 (via API or locally). It accepts the technical specifications, loads the knowledge base (brand book, country labeling rules), and manages other modules.

Visualization module (Food zones and Mockups): Integration with Flux.1 (Dev/Schnell) or Stable Diffusion XL via ControlNet. This will allow generating ultra-realistic ingredients (pistachio, coconut) and accurately fitting them into the packaging graphic grid without blurring.

Labeling and localization module: Automatic translation of ingredients and nutritional information into Thai, Japanese, or Ukrainian using LLM, with compliance checks for regulations (font sizes, allergen warnings).

Vector engine (Print generation): Since AI cannot produce clean vector .AI or .PSD files with layers, Hermes will manage a server library (e.g., Sharp or SVG/Canvas templating). The AI will generate backgrounds and texts, and the system will compile them into a final high-resolution file with bleed.
My GitHub: https://github.com/onyx144

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Hello! Ready to collaborate. I have experience working with AI agents. I offer quality and fast work. Write to me.

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We have done something similar in production: AI agents on Claude/GPT-4o with RAG based on a knowledge base, content generation, and visuals. We will do what you describe. Relevant cases: Winbix.AI (multi-agent platform with RAG and knowledge base, $2K MRR, 30+ paying clients), BrandSync AI (production pipeline with AI content generation), BotFusion AI (AI agents on 19+ platforms).

We will implement according to your task:

Design and concept generation: Claude for packaging concept based on the specifications, design options, adaptation for product lines (colors, flavors, names). A text request ("Create a new flavor Protein Bar Pistachio Coconut in the FitWin style") is processed by the agent.

Brand book as a knowledge base: RAG based on your brand book (colors, fonts, rules, brand elements) to maintain a consistent style across all generations.

Labeling: formation of blocks (composition, nutritional value, recommendations, warnings, manufacturer data, barcodes, QR codes, certification marks) with adaptation to the requirements of different countries (EU, Thailand, Ukraine) and auto-translation of language versions (EN/UK/TH/JP).
…
Visuals: AI generation through Flux/SDXL for food zones, ingredients, advertising visuals, product mockups for marketplaces and social media, POS materials, and banners based on the design.

Working with layouts: uploading source files (PNG, JPG, PSD, AI, PDF), replacing texts, flavors, characteristics, series of packaging according to a single template without changing the brand style.

Production files: preparation for printing considering technical requirements (bleeds, safe zones, sizes, placement of mandatory information), generating specifications for the printing house.

Stack: Claude Sonnet 4.6 + GPT-4o for logic and text, Flux/SDXL for image generation, RAG on pgvector based on the brand book, FastAPI backend, web interface for working with text requests.

Quentar, a studio of 6 developers (UTC+2). For the project: AI/Python engineer, integration and interface developer, QA.

Portfolio: winbixai.com/en/startups. We will send a Loom overview of Winbix.AI with AI agents and RAG in private.

Guarantee: 30 days post-launch support with AI calibration at our expense.

Questions:

Is the brand book and library of brand elements already structured (vector, guidelines), or are we building the knowledge base from scratch?
What is the priority for the first stage: labeling with multilingual support or generation of visuals and concepts?
For how many markets and languages is labeling needed at the start?

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For your task, I see a solution in the form of an AI agent with a knowledge base based on the brand book, packaging templates, and labeling rules for different markets, which will be able to create new concepts, adapt existing layouts, and automatically generate the necessary information blocks.

I am engaged in the development of AI systems and agents based on GPT, Claude, Gemini, and n8n. I have implemented projects for AI generation of commercial product photos, AI stylists, systems for working with large volumes of content, and automation of business processes.

Do you have a ready brand book, a library of source layouts, and examples of packaging that the agent should use as a reference?

I am ready to connect to the project and work out the architecture of the solution in detail right now.

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Zlatoslava, hello

Important: in the phrase "AI agent as a professional packaging designer," there is a part that cannot be honestly promised as fully automated: generating print-ready layouts (AI/PDF with bleed, safe zones, fonts, barcodes, certification) without human involvement and without checks is a risk of errors and legal issues. However, it is feasible to create a working system where AI handles 80% of the routine, and a human performs the final check and print release.

I can create an AI agent for designing sports nutrition packaging that will speed up the development of new designs, labels, and adaptations for different markets—while maintaining brand style and quality control.
I develop such solutions as a system of "templates + knowledge base + generation + verification" to make it suitable for real production, not just pretty pictures.

If you already have a ready website, please send the link in private so I can familiarize myself with the assortment. In what format do you currently have the packaging source files and brand guide—Figma or Illustrator (AI), and do you have ready master templates for the main form factors (can/bag/bar)?

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Greetings. The task is clear, but if we do it purely with generative AI, there will be a problem: neural networks excel at drawing backgrounds but distort logos, turn small text into mush, and break barcodes. Such a layout will not be accepted by the printing house.

A hybrid approach is needed here. The agent will use AI to generate graphics and adapt colors to new tastes, while all the technical parts—logos, nutritional tables, labels in different languages—will be applied programmatically on a clear grid. In the end, you will receive print-ready files without distortions and misaligned elements.

I am ready to implement such a pipeline. Please let me know in what format your original layouts are currently stored?

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Hello! Are you planning to use an existing brand book for the agent in the form of files or a text description?

I will be able to specify the terms and budget more accurately in personal correspondence.

Here’s how I will implement this project:
1. I will set up the agent's knowledge base based on your brand book and library of elements.
2. I will integrate AI generation to create packaging designs and labels based on text prompts.
3. I will ensure automatic adaptation of layouts for different markets, languages, and printing requirements.

… Thank you for considering my proposal. I look forward to the opportunity to collaborate with you!

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Good day. I am interested in your order. I have over 10 years of experience in web development. For clarification on the technology stack for development, please write in private messages.

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Hello, I worked on creating an AI agent for automating food packaging design - the system generated 15+ design options in 3 minutes while adhering to branding and adapting for 8 countries.

How do you plan to train the agent to distinguish the technical requirements of different markets - for example, QR code sizes for Thailand vs the EU?

I suggest we get in touch, I will provide you with free technical consultation and we can outline a development plan + I will tell you about my team! ✨

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