AI Archives - DGsthal

Winter Nights and Neural Networks: How AI Works in Silence

When winter nights stretch longer and the world slows down, it feels like everything has paused. Roads are empty, notifications stop buzzing, and humans finally rest.But this silence hides a…

Payal Ganguly January 14, 2026

Green AI – Making AI Training and Inference More Energy-Efficient

Artificial Intelligence is transforming industries — from healthcare and finance to marketing and education. But as AI models grow larger and more powerful, they also consume massive amounts of energy.…

Payal Ganguly January 7, 2026

AI Blog

Enterprise AI Agents: Redefining Productivity and Process Automation

Artificial intelligence in enterprises has moved far beyond chatbots and analytics dashboards. Organizations are now deploying Enterprise AI Agents—intelligent systems capable of planning, reasoning, and executing tasks across business operations.…

Payal Ganguly December 31, 2025

Temporal AI: Learning from Time-Series Data in Finance and IoT

Data doesn’t exist in isolation—it flows over time.Stock prices, sensor readings, energy consumption, transaction logs, and network traffic all change second by second. This is where Temporal AI comes in.…

Payal Ganguly December 24, 2025

AI Generative AI

OpenAI o1 vs Gemini 2 vs Claude 3.5 — The Great AI Model Showdown of 2025

2025 is the year AI models stopped being “chatbots” and started becoming thinking systems, multimodal engines, and enterprise-grade assistants. Three models dominate the conversation: OpenAI o1 — reasoning-first AI Gemini…

Payal Ganguly December 18, 2025

AI-Powered Marketing Funnels: Smarter ToFu, MoFu, BoFu Automation

Marketing funnels have evolved more in the last two years than in the last twenty.Why?Because AI isn’t just assisting marketing anymore—AI is running it. From generating awareness content to personalizing…

Payal Ganguly December 10, 2025

$What AI Can SMEs Build Easily Using Open Source? 1. AI Customer Support Chatbot (with RAG) Answers FAQs Reduces support workload Works with your policy docs, product guides Tools: Llama 3 + ChromaDB + LangChain 2. Internal AI Knowledge Base Search across company documents instantly. Tools: LlamaIndex + FAISS + Llama 3 3. Sales & Marketing Automation AI Lead scoring Email generation Market research Proposal writing Tools: Mixtral + LangGraph Agents 4. AI Agents for Repetitive Work AI that takes actions, not just answers: Filling CRM entries Generating reports Scraping data Monitoring tasks Tools: CrewAI, AutoGen, LangGraph 5. AI-Powered Analytics (Near Zero Cost) Demand forecasting Churn prediction Sales trend analysis Tools: Python + Prophet + Scikit-learn 💡 How SMEs Can Start With AI (Simple 4-Step Plan) Step 1: Identify High-Impact Use Cases Which tasks consume manual effort? Support Sales Operations Marketing Documentation Pick one with daily impact. Step 2: Start With Open-Source Tools Recommended starter kit: Task Open-Source Tools Cost Chatbot Llama 3 + ChromaDB Free RAG Search LlamaIndex + FAISS Free AI Agents LangGraph / CrewAI Free Analytics Python + scikit-learn Free Step 3: Deploy on Local or Low-Cost Cloud Use Ollama or a cheap cloud VM. Cost: ₹500–₹2000/month (or $8–$25). Step 4: Expand With Fine-Tuning Once your system works: Fine-tune with company data Improve accuracy Build custom workflows 📌 Why Open-Source AI Is Perfect for SMEs in 2025 ✔ No licensing fees ✔ Full control over data ✔ Customization flexibility ✔ Enterprise-grade outputs ✔ Works with small teams ✔ Avoids vendor lock-in ✔ Can run on affordable hardware Open-source AI levels the playing field — now SMEs can compete with enterprise capabilities without enterprise costs. 🔚 Conclusion AI is no longer a luxury. With open-source tools, SMEs can build: powerful chatbots internal AI search engines automated workflows predictive analytics AI agents …all at a fraction of the cost big companies spend. 2025 is the year when AI becomes accessible to everyone — especially SMEs.$

How SMEs Can Afford Enterprise-Grade AI Using Open-Source Tools (2025 Guide)

Artificial Intelligence was once something only big enterprises could afford. High licensing fees, complex MLOps workflows, and large data teams made AI inaccessible for small and medium-sized businesses (SMEs). But…

Payal Ganguly December 3, 2025