LLM Observability: Production Traces, Costs, Quality, and Alerts
A customer assistant functions efficiently by providing immediate feedback with the HTTP 200 status code while also providing outdated information on refund policies. The infrastructure dashboard remains unperturbed. However, the customer is left in the dark with incorrect information. LLM observability connects each request with information on its execution duration, the cost of its execution, […]
Niraj Salot
What Is a Private LLM? Benefits, Use Cases & Business Need
Every enterprise using generative AI eventually asks the same question: where does our data actually go once we hit “send” on a prompt? For a growing number of companies, the answer is a third-party API, processed on infrastructure they don’t control; it isn’t good enough anymore. That’s driving renewed interest in private LLMs: language models […]
Anshum Shankhdhar
RAG vs Fine-Tuning: Which AI Approach Is Best for Enterprise LLM Applications?
More enterprises are putting large language models into real workflows now — customer support, internal search, decision support. Once a team gets past the first proof of concept, one question comes up almost every time: do we build this with Retrieval-Augmented Generation (RAG), or do we fine-tune a model on our own data? Both approaches […]
Pranav Lakhani
Custom LLM Integration: How LLM is Game Changer for Enterprise Operations?
Businesses are transitioning from generic AI-based applications to custom-built large language models (LLMs). These models are trained on each organization’s unique data, processes, and industry-specific vernacular. The use of custom LLM solutions has transitioned from being an option to becoming a requisite element to enhance organizational efficiency, expedite innovation, and maintain a competitive edge. Here […]
Niraj SalotLet’s Turn Ideas into Reality!
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