LLM
Unlock the power of AI with us. We Craft AI Solutions using LLM to make AI approachable for your business.
Unlock the power of AI with us. We Craft AI Solutions using LLM to make AI approachable for your business.
Coding agents write a convincing first draft, not finished code. These are the coding agents best practices that keep engineering teams in control: verify every response, own the docs the agent generates, trace the logic before pushing, and never ship code you have not read.
A-CX explores how employee-built AI agents and applications are transforming organizations and why they need a governance foundation to reach production. This post introduces the A-CX AI Nexus, a set of cloud-agnostic libraries that provide the control plane organizations need to deploy agentic AI securely, reliably, and at scale.
A-CX built its own governed AI tooling instead of relying on unverified public plugins. This post covers the decisions, the architecture, the feedback loop, and where AI genuinely moves the needle.
A major challenge in integrating LLMs with other applications is the lack of structure in chat responses. OpenAI Functions and Azure Assistants can be used to help structure data for programs to use.
Improve the quality of retrieval augmented generation responses using classification to select better data and system messages.
LLMs only have access to information about things they were trained on, which limits their capabilities. This can be avoided by using Retrieval Augmented Generation, or RAG for short.