CREDEMA AG

CREATE - DEVELOP - MARKET your online presence with the right set of integrated digital tools…CREDEMA…more than just a CRM

[Nutaan AI @Nutaan_AI]

🚀 Big Update: Nutaan AI Just Got Better! It’s your Nutaan 2.0.

We've completely improved the Nutaan AI experience to make it faster, simpler, and more user-friendly than ever.

✨ What's New?

✅ Cleaner & Easier Dashboard
✅ Improved AI Calling Experience
✅ Faster Setup & Configuration
✅ Better Website Chat Widget
✅ Enhanced AI Assistant Performance
✅ NEW: Batch AI Calling 🎉

Now you can launch AI-powered bulk calling campaigns, engage thousands of contacts automatically, and scale outreach without increasing your team size.

Whether you're using Nutaan for sales, support, lead qualification, appointment booking, or customer engagement, the platform is now more powerful and easier to use.

📺 If you haven't already, check out all the videos on this channel to discover the latest features, tutorials, and use cases.

https://t.co/NpJHd8X4Fz

#Nutaan #AICalling #BatchCalling #VoiceAI #BusinessAutomation #AIChat #CustomerSupport #LeadGeneration #SalesAutomation #ArtificialIntelligence

[CREDEMA AG @CredemaAG]

@perplexity_ai @NVIDIAAI @nvidia And it is amazing

[CREDEMA AG @CredemaAG]

@nalinrajput23 Perplexity

[CREDEMA AG @CredemaAG]

@nalinrajput23 And you did not even mention the Gemini derived product range!

[CREDEMA AG @CredemaAG]

@_devJNS 😂👍

[CREDEMA AG @CredemaAG]

@ChrisLaubAI Made the same experience

[CREDEMA AG @CredemaAG]

@RMHildebrandt CRM

[CREDEMA AG @CredemaAG]

@razib_ul47671 AI

[CREDEMA AG @CredemaAG]

@WorkflowWhisper ANTIGRAVITY

[CREDEMA AG @CredemaAG]

@maria_wats8492 Yes

[CREDEMA AG @CredemaAG]

@milesdeutscher Great summary but why not mention Goggle Ao Studio?

[CREDEMA AG @CredemaAG]

@GoogleAIStudio The Google AI Studio productions are stunning and wish there would be an easy way to process development into scalable projects that are way to deploy. GitHub connection causes issues, deployments cause issues database connections are not stable…a pity really

[CREDEMA AG @CredemaAG]

@devops_nk @levelsio 😂👍

[CREDEMA AG @CredemaAG]

@LoufactsIGB @elonmusk Well answered!

[CREDEMA AG @CredemaAG]

@v_computer @danielgrossmann Great work!!!!

[CREDEMA AG @CredemaAG]

@goyalshaliniuk Great summary!

[Shalini Goyal @goyalshaliniuk]

RAG is not just one technique, it is an entire ecosystem of intelligence.

From context-aware assistants to domain-specific systems, here are 16 types of RAG models shaping the next wave of AI innovation -

1. Standard RAG
The foundation of all RAG systems - combines retrieval and generation for question answering and knowledge synthesis.

2. Agentic RAG
Empowers AI agents to retrieve and act autonomously, perfect for assistants that need dynamic, tool-based reasoning.

3. Graph RAG
Uses knowledge graphs for relational reasoning - ideal for expert systems in law, medicine, and semantic search.

4. Modular RAG
Breaks retrieval, reasoning, and generation into independent components - enabling collaborative, scalable AI workflows.

5. Memory-Augmented RAG
Adds persistent external memory for context retention, powering long-term chatbots and personalized experiences.

6. Multi-Modal RAG
Processes text, images, and audio together - perfect for video summarization, captioning, and multi-modal AI tools.

7. Federated RAG
Enables privacy-preserving retrieval from decentralized sources, used in healthcare and secure enterprise systems.

8. Streaming RAG
Performs real-time retrieval and generation, ideal for financial dashboards, live feeds, and social media monitoring.

9. ODQA RAG (Open-Domain QA)
Handles large, diverse datasets - ideal for search engines and intelligent virtual assistants.

10. Contextual Retrieval RAG
Maintains session-level awareness, great for conversational AI and customer support chatbots.

11. Knowledge-Enhanced RAG
Integrates structured domain data, useful for legal, educational, and professional knowledge applications.

12. Domain-Specific RAG
Custom-tailored for specific industries - like finance, healthcare, or legal analytics.

13. Hybrid RAG
Combines multiple retrieval approaches, bridging structured and unstructured data for high precision.

14. Self-RAG
Introduces self-reflection to refine its own answers, enabling AI models to fact-check and improve reasoning autonomously.

15. HyDE RAG (Hypothetical Document Embeddings)
Generates hypothetical documents to guide retrieval, excellent for complex or niche query contexts.

16. Recursive / Multi-Step RAG
Performs multiple retrieval-generation loops, enabling advanced problem-solving and reasoning chains.

From simple retrievals to self-improving AI reasoning loops, RAG is evolving fast.
Which type do you think will dominate enterprise AI systems in 2026?

[Nas @Nas_tech_AI]

A YouTuber earns:

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10M views = $30,000
100M views = $300,000+

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1. Follow (Must)
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[CREDEMA AG @CredemaAG]

@perplexity_ai Any plans for iOS?

[CREDEMA AG @CredemaAG]

@EcosystemMonad 6