December 5, 2025
10 minutes read
Fine-Tuning vs RAG: Different Techniques for Adapting LLMs
Fine-Tuning specializes LLMs with domain expertise, while RAG adds real-time, verifiable context to create accurate and compliant enterprise-ready AI.
Anand Reddy KS
CTO & Co-founder at Tericsoft
November 27, 2025
12 minutes read
Natural Language Processing (NLP): A Comprehensive Guide
Natural Language Processing (NLP) combines linguistics & machine learning to transform unstructured text and speech into structured representations.
Anand Reddy KS
CTO & Co-founder at Tericsoft
November 25, 2025
10 minutes read
What Is Microservices Architecture and Why It Matters?
Microservices architecture is a modular approach to software design where independent services handle specific tasks, enabling speed and scalability.
Abdul Rahman Janoo
Co-founder & CEO at Tericsoft
November 22, 2025
12 minutes read
How Are Enterprise LLMs Accelerating Workflow Efficiency?
Enterprise LLMs build private, domain-specific AI brains that boost productivity, reduce cycle times, and deliver 3.7× ROI across regulated workflows.
Anand Reddy KS
CTO & Co-founder at Tericsoft
November 13, 2025
13 minutes read
What Is Fine-Tuning? How It Works and Why It’s Important
Fine‑Tuning adapts LLMs to your data, cutting hallucinations by 90%, boosting domain accuracy & turning AI into a compliant, brand‑aligned expert.
Anand Reddy KS
CTO & Co-founder at Tericsoft
November 10, 2025
12 minutes read
Contextual Retrieval in AI: How It Works and Why It Matters
Contextual Retrieval in AI refines RAG systems by understanding query intent, cutting failed retrievals by 49% and improving answer accuracy by 67%.
Anand Reddy KS
CTO & Co-founder at Tericsoft
November 4, 2025
10 minutes read
Technology as a Service: What It Means for Modern Businesses
Technology as a Service helps businesses shift from CapEx to OpEx, reduce IT burden, eliminate obsolescence & scale tech needs on-demand with ease.
Abdul Rahman Janoo
Co-founder & CEO at Tericsoft
October 31, 2025
11 minutes read
What is RAG (Retrieval-Augmented Generation) in Contextual AI?
RAG (Retrieval-Augmented Generation) connects LLMs to your live data, enabling accurate, citable answers and reducing hallucinations by up to 67%.
Anand Reddy KS
CTO & Co-founder at Tericsoft
