Tiledesk Design Studio

Q: "I modelli linguistici di grandi dimensioni possono girare su infrastruttura privata?"

"Sì. Modelli open source come LLaMA, Mistral, DeepSeek e Qwen possono funzionare on-premise o su cloud europeo. Questi modelli raggiungono prestazioni paragonabili a GPT-4 per la maggior parte dei task aziendali, con il vantaggio della completa sovranità sui dati. Lo stack PRISMA di HTX è progettato per implementare questi modelli per le PMI europee."

Q: "Quale LLM è migliore per uso aziendale?"

"Il modello migliore dipende dal caso d'uso. Per analisi documenti e chat, modelli come Mistral e LLaMA eccellono. Per analisi dati, DeepSeek offre forte ragionamento. L'approccio di HTX è model-agnostic: ORCA supporta più modelli così puoi scegliere il più adatto senza vendor lock-in."

Articoli Interessanti - This article is part of a series.

Part : Qwen

Part : Introducing Claude Opus 4.7 Anthropic

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

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Part : Show HN: 1-Bit Bonsai, the First Commercially Viable 1-Bit LLMs

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

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

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

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Part : Introducing Mistral Small 4 | Mistral AI

Part : GitHub - andrewyng/context-hub

Part : Coding my Handwriting — Amy Goodchild

Part : GitHub - jundot/omlx: LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the mac

Part : My chief of SEO, Claude Cowork

Part : Building AI Coding Agents for the Terminal: Scaffolding, Harness, Context Engineering, and Lessons Learned

Part : GitHub - NousResearch/hermes-agent: The agent that grows with you

Part : GitHub - bytedance/deer-flow: An open-source SuperAgent harness that researches, codes, and creates. With the help of sandboxes, m

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Part : GitHub - z-lab/paroquant: [ICLR 2026] ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference

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Part : GitHub - Search code, repositories, users, issues, pull requests...: Altered state slash commands for Claude Code. 12 substance-themed personality modes that change how

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Part : The Anthropic Economic Index Anthropic

Part : dots.ocr: Multilingual Document Layout Parsing in a Single Vision-Language Model

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Part : DeepSite v2 - a Hugging Face Space by enzostvs

Part : How to Use Claude Code Subagents to Parallelize Development

Part : Show HN: CLAVIER-36 – A programming environment for generative music

Part : Small models are the future of agentic ai

Part : Kimi K2: Open Agentic Intelligence

Part : Introducing Qwen3-Max-Preview (Instruct)

Part : Scientific Paper Agent with LangGraph

Part : Anthropic's Interactive Prompt Engineering Tutorial

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Part : swiss-ai/Apertus-70B-2509 · Hugging Face

Part : Making a font of my handwriting · Chameth.com

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Part : LoRAX: Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs

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Part : [2504.19413] Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory

Part : Apertus 70B: Truly Open - Swiss LLM by ETH, EPFL and CSCS

Part : HumanLayer

Part : PageIndex: Document Index for Reasoning-based RAG

Part : Deploying DeepSeek on 96 H100 GPUs

Part : Claude Code: A Highly Agentic Coding Assistant - DeepLearning.AI

Part : DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning

Part : [2508.15126] aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists

Part : Alexander Kruel - Links for 2025-08-24

Part : DSPy

Part : AI Agents for Beginners - A Course

Part : Turning Claude Code into my best design partner

Part : How to build a coding agent

Part : This Article

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Part : Data Formulator: Create Rich Visualizations with AI

Part : browser-use/web-ui

Part : Casper Capital - 100 AI Tools You Can’t Ignore in 2025...

Part : Parlant

Part : CS294/194-196 Large Language Model Agents | CS 194/294-196 Large Language Model Agents

Part : Show HN: Whispering – Open-source, local-first dictation you can trust

Part : Fallinorg v1.0.0-beta

Part : dokieli

Part : paperetl

Part : Automatically annotate papers using LLMs

Part : My AI Had Already Fixed the Code Before I Saw It

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Part : Claudia – Desktop companion for Claude code

Part : Show HN: Fallinorg - Offline Mac app that organizes files by meaning

Part : Focalboard

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Part : Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting

Part : Prava - Teaching GPT‑5 to use a computer

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#### Fonte

Tipo: GitHub Repository
Link originale: https://github.com/Tiledesk/design-studio
Data pubblicazione: 2025-09-04

Sintesi
#

WHAT - Tiledesk Design Studio è una piattaforma open-source, no-code per creare chatbot e app conversazionali. Utilizza un approccio grafico flessibile e integra LLM/GPT AI per automatizzare conversazioni e compiti amministrativi.

WHY - È rilevante per il business AI perché permette di creare rapidamente chatbot avanzati senza competenze di programmazione, riducendo i costi di sviluppo e accelerando il time-to-market.

WHO - Gli attori principali sono Tiledesk, una startup che sviluppa soluzioni di conversational AI, e la community open-source che contribuisce al progetto.

WHERE - Si posiziona nel mercato delle piattaforme di conversational AI, competendo con strumenti come Voiceflow e Botpress, offrendo un’alternativa open-source e no-code.

WHEN - Il progetto è attualmente in fase di sviluppo attivo, con una comunità in crescita e un ecosistema di integrazioni in espansione. È un trend emergente nel settore delle soluzioni AI no-code.

BUSINESS IMPACT:

Opportunità: Integrazione con il nostro stack esistente per offrire soluzioni di conversational AI ai clienti senza competenze tecniche.
Rischi: Competizione con soluzioni consolidate come Voiceflow e Botpress.
Integrazione: Possibilità di estendere le funzionalità del nostro prodotto principale con le capacità di Tiledesk Design Studio.

TECHNICAL SUMMARY:

Core technology stack: Angular, Node.js, integrazioni con LLM/GPT AI.
Scalabilità: Buona scalabilità grazie all’approccio grafico e alle integrazioni API, ma dipendente dalla maturità della community open-source.
Differenziatori tecnici: Approccio no-code, integrazione con LLM/GPT AI, e un ecosistema di integrazioni flessibile.

Casi d’uso
#

Private AI Stack: Integrazione in pipeline proprietarie
Client Solutions: Implementazione per progetti clienti
Development Acceleration: Riduzione time-to-market progetti
Strategic Intelligence: Input per roadmap tecnologica
Competitive Analysis: Monitoring ecosystem AI

Risorse
#

Link Originali
#

Tiledesk Design Studio - Link originale

Articolo segnalato e selezionato dal team Human Technology eXcellence elaborato tramite intelligenza artificiale (in questo caso con LLM HTX-EU-Mistral3.1Small) il 2025-09-04 19:03 Fonte originale: https://github.com/Tiledesk/design-studio

Il Punto di Vista HTX
#

Questo tema è al centro di ciò che costruiamo in HTX. La tecnologia discussa qui — che si tratti di agenti AI, modelli linguistici o elaborazione documenti — rappresenta esattamente il tipo di capacità di cui le aziende europee hanno bisogno, ma implementata alle proprie condizioni.

La sfida non è se questa tecnologia funziona. Funziona. La sfida è implementarla senza inviare i dati aziendali a server USA, senza violare il GDPR e senza creare dipendenze da fornitori da cui non puoi uscire.

Per questo abbiamo costruito ORCA — un chatbot aziendale privato che porta queste capacità sulla tua infrastruttura. Stessa potenza di ChatGPT, ma i tuoi dati non escono mai dal tuo perimetro. Nessun costo per utente, nessuna fuga di dati, nessun problema di compliance.

Vuoi sapere quanto è pronta la tua azienda per l’AI? Fai il nostro Assessment gratuito della AI Readiness — 5 minuti, report personalizzato, roadmap operativa.

FAQ

I modelli linguistici di grandi dimensioni possono girare su infrastruttura privata?

Sì. Modelli open source come LLaMA, Mistral, DeepSeek e Qwen possono funzionare on-premise o su cloud europeo. Questi modelli raggiungono prestazioni paragonabili a GPT-4 per la maggior parte dei task aziendali, con il vantaggio della completa sovranità sui dati. Lo stack PRISMA di HTX è progettato per implementare questi modelli per le PMI europee.

Quale LLM è migliore per uso aziendale?

Il modello migliore dipende dal caso d'uso. Per analisi documenti e chat, modelli come Mistral e LLaMA eccellono. Per analisi dati, DeepSeek offre forte ragionamento. L'approccio di HTX è model-agnostic: ORCA supporta più modelli così puoi scegliere il più adatto senza vendor lock-in.

Articoli Interessanti - This article is part of a series.

Part : Qwen

Part : Introducing Claude Opus 4.7 Anthropic

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 LLMs

Part : PrismML — Concentrating intelligence

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

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

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

Part : GitHub - 666ghj/MiroFish: A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物

Part : Introducing Mistral Small 4 | Mistral AI