PRODUCT
Solving the LLM Infrastructure Bottleneck: Enabling Scale
Discover how we solve the LLM infrastructure bottleneck and optimize AI deployments with adaptive infrastructure.
LEARNING
Beyond Context Windows: Unleashing True Autonomous AI
How our autonomous agents conquer massive data, deliver 200x ROI, and prevent critical errors with breakthroughs in memory, persistence, and agent...
PRODUCT
How We Built Truly Autonomous Agents
From while loops to sophisticated tools, discover how we built the infrastructure for enterprise AI agents
PRODUCT
Solving the Content Conundrum: Semantic DocPrep for GenAI
Introducing Vertesia's Semantic DocPrep API service that eliminates LLM hallucinations and generates accurate, relevant results.
NEWS
Vertesia: A New Chapter in AI-Powered Innovation
Composable is now Vertesia, a name that embodies our future-focused mission, reflecting our commitment to accelerating AI adoption.
NEWS
Vertesia Wins 2024 Innovation Award from Deep Analysis
We are one of five winners of the 2024 Innovation Award from Deep Analysis, recognized for solving real-world business challenges with GenAI.
LEARNING
Is Documentation Generation and Maintenance a Good Use Case for LLMs?
Documentation generation and maintenance is a good use case for LLM-powered tasks when paired with a platform a approach.
NEWS
Vertesia included in Google's AI First Accelerator Program
We've joined the latest cohort of startups in Google's AI First Accelerator program.
LLM
RAG is about Context not Vectors
RAG means Retrieval-Augmented Generation and it provides context to Large Language Models.
LLM
LLMs don’t hallucinate, they make mistakes.
Do LLMs hallucinate? No, LLMs make mistakes but there are strategies to mitigate the impact of these mistakes.