AI Model & Technology
When your voice bot calls a customer and they don't pick up, something critical happens: the call goes to voicemail. If your bot doesn't detect this correctly, the customer never receives your message. That appointment reminder, payment alert, or urgent callback? Gone. Today, calls getting kicked
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What is the tech stack for agentic AI? The tech stack for agentic AI comprises five core components: Large Language Models (LLMs) like Llama or GPT for reasoning, Automatic Speech Recognition (ASR) systems such as Deepgram for voice input, Text-to-Speech (TTS) engines like ElevenLabs for voice output, vector databases for
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TL;DR: If you care about tone, latency, and cost, don’t keep stuffing GPT-4o with giant prompts. Fine-tune a small model on synthetic call-style Q&A once, then ship it. A 1B Llama hit ~97% “conversational” answers vs. GPT-4o’s ~29% with prompting alone. The paper https://arxiv.
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What is the tech stack for agentic AI? The tech stack for agentic AI consists of four core layers: foundation models (LLMs like Llama or GPT-4), speech processing (STT/TTS engines like Deepgram and ElevenLabs), memory systems (vector databases and knowledge bases), and orchestration frameworks (LangChain/LangGraph). These components work
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Understanding AI Models and Technology: A Complete Enterprise Guide to Agentic AI Architecture As enterprises accelerate their adoption of agentic AI, understanding the underlying technology becomes crucial for successful implementation. With 65% of organizations now running AI pilots—up from 37% in Q4 2024—technical leaders need deep insights into
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Understanding AI Models and Technology: What Powers Enterprise Agentic AI Platforms? As enterprises race to implement agentic AI solutions, technical decision-makers face a critical challenge: understanding the complex technology stack that powers these autonomous systems. With 65% of enterprises having AI pilots underway in Q1 2025, the question isn'
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Understanding AI Models and Technology: A Complete Enterprise Guide to Agentic AI Architecture Enterprise adoption of agentic AI is accelerating at an unprecedented pace, with 65% of organizations running pilots in Q1 2025. Yet beneath the surface of this technological revolution lies a complex ecosystem of models, architectures, and integration
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What is an LLM in agentic AI? Large Language Models (LLMs) serve as the cognitive foundation of agentic AI systems, enabling autonomous reasoning, decision-making, and natural language understanding. In enterprise deployments, LLMs like Llama 3, GPT-4, and Claude process complex queries, maintain context across conversations, and generate human-like responses while
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Understanding AI Models and Technology: The Enterprise Guide to Agentic AI Architecture The landscape of enterprise AI has fundamentally shifted. While 65% of enterprises are running AI pilots in 2024-2025, only 11% have achieved full deployment—a gap that often stems from misunderstanding the underlying technology stack. For BPOs seeking
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What is the tech stack for agentic AI? The modern agentic AI tech stack comprises multiple specialized components working in concert: LLMs for reasoning, STT/TTS engines for voice interactions, vector databases for knowledge retrieval, and orchestration frameworks for workflow management. Enterprise deployments typically combine best-in-class solutions like Llama models,
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What is the Tech Stack for Enterprise Agentic AI? The modern agentic AI tech stack comprises multiple integrated layers including LLMs for cognitive processing, speech recognition systems like Deepgram, TTS engines such as 11 Labs, knowledge bases for context, and orchestration platforms. This architecture requires careful selection of components optimized