Tiledesk Design Studio

Q: "Can large language models run on private infrastructure?"

"Yes. Open-source models like LLaMA, Mistral, DeepSeek, and Qwen can run on-premise or on European cloud. These models achieve performance comparable to GPT-4 for most business tasks, with the advantage of complete data sovereignty. HTX's PRISMA stack is designed to deploy these models for European SMEs."

Q: "Which LLM is best for business use?"

"The best model depends on your use case. For document analysis and chat, models like Mistral and LLaMA excel. For data analysis, DeepSeek offers strong reasoning. HTX's approach is model-agnostic: ORCA supports multiple models so you can choose the best fit without vendor lock-in."

Articoli Interessanti - This article is part of a series.

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#### Source

Type: GitHub Repository Original link: https://github.com/Tiledesk/design-studio Publication date: 2025-09-04

Summary
#

WHAT - Tiledesk Design Studio is an open-source, no-code platform for creating chatbots and conversational apps. It uses a flexible graphical approach and integrates LLM/GPT AI to automate conversations and administrative tasks.

WHY - It is relevant for AI business because it allows for the rapid creation of advanced chatbots without programming skills, reducing development costs and accelerating time-to-market.

WHO - The main players are Tiledesk, a startup that develops conversational AI solutions, and the open-source community that contributes to the project.

WHERE - It positions itself in the conversational AI platform market, competing with tools like Voiceflow and Botpress, offering an open-source and no-code alternative.

WHEN - The project is currently in active development, with a growing community and an expanding ecosystem of integrations. It is an emerging trend in the no-code AI solutions sector.

BUSINESS IMPACT:

Opportunities: Integration with our existing stack to offer conversational AI solutions to clients without technical skills.
Risks: Competition with established solutions like Voiceflow and Botpress.
Integration: Possibility of extending the functionalities of our main product with the capabilities of Tiledesk Design Studio.

TECHNICAL SUMMARY:

Core technology stack: Angular, Node.js, integrations with LLM/GPT AI.
Scalability: Good scalability thanks to the graphical approach and API integrations, but dependent on the maturity of the open-source community.
Technical differentiators: No-code approach, integration with LLM/GPT AI, and a flexible ecosystem of integrations.

Use Cases
#

Private AI Stack: Integration in proprietary pipelines
Client Solutions: Implementation for client projects
Development Acceleration: Reduction in project time-to-market
Strategic Intelligence: Input for technological roadmap
Competitive Analysis: Monitoring AI ecosystem

Resources
#

Original Links
#

Tiledesk Design Studio - Original link

Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-04 19:03 Original source: https://github.com/Tiledesk/design-studio

The HTX Take
#

This topic is at the heart of what we build at HTX. The technology discussed here — whether it’s about AI agents, language models, or document processing — represents exactly the kind of capability that European businesses need, but deployed on their own terms.

The challenge isn’t whether this technology works. It does. The challenge is deploying it without sending your company data to US servers, without violating GDPR, and without creating vendor dependencies you can’t escape.

That’s why we built ORCA — a private enterprise chatbot that brings these capabilities to your infrastructure. Same power as ChatGPT, but your data never leaves your perimeter. No per-user pricing, no data leakage, no compliance headaches.

Want to see how ready your company is for AI? Take our free AI Readiness Assessment — 5 minutes, personalized report, actionable roadmap.

FAQ

Can large language models run on private infrastructure?

Yes. Open-source models like LLaMA, Mistral, DeepSeek, and Qwen can run on-premise or on European cloud. These models achieve performance comparable to GPT-4 for most business tasks, with the advantage of complete data sovereignty. HTX's PRISMA stack is designed to deploy these models for European SMEs.

Which LLM is best for business use?

The best model depends on your use case. For document analysis and chat, models like Mistral and LLaMA excel. For data analysis, DeepSeek offers strong reasoning. HTX's approach is model-agnostic: ORCA supports multiple models so you can choose the best fit without vendor lock-in.

Articoli Interessanti - This article is part of a series.

Part : GitHub - arman-bd/guppylm: A ~9M parameter LLM that talks like a small fish.

Part : Embarrassingly Simple Self-Distillation Improves Code Generation

Part : Show HN: 1-Bit Bonsai, the First Commercially Viable 1-Bit Large Language Models

Part : PrismML — Concentrating Intelligence

Part : GitHub - microsoft/VibeVoice: Open-Source Voice AI

Part : GitHub - karpathy/autoresearch: AI agents automatically conducting research on single-GPU nanochat training

Part : GitHub - Pinperepette/snakebite: Detect malicious PyPI packages using heuristic analysis and LLM-powered filtering to uncover credentials

Part : GitHub - 666ghj/MiroFish: A Simple and Universal Swarm Intelligence Engine, Predicting Anything. A concise and universal swarm intelligence engine, predicting everything.

Part : Introducing Mistral Small 4 | Mistral AI

Part : GitHub - andrewyng/context-hub

Part : Coding My Handwriting — Amy Goodchild