Generative AI refers to models that create new content — text, images, code — by learning patterns from existing data, powering everything from chatbots to automated content generation.
Nexla feeds generative AI applications governed, structured data instead of raw, ungoverned sources, reducing hallucinations and improving output quality for GenAI use cases.
Enterprise AI agents fail when the context behind their decisions is incomplete, stale, or conflicting. Context engineering ensures agents receive accurate, permission-aware runtime context for reliable decisions.
Explore how a multimodal AI pipeline built with NVIDIA models, Nebius infrastructure, and Nexla orchestration converts social media travel videos into structured itineraries.
Reusable data products unify databases, PDFs, and logs with metadata, validation, and lineage to enable join-aware RAG retrieval for reliable GenAI applications.
Agentic RAG systems fail when data is fragmented, stale, or inconsistent. Learn how AI-ready data products with standardized schemas, governance, and retrieval metadata enable reliable, scalable RAG applications.
AI systems fail when context doesn’t scale. This article explains the limits of context graphs, why static relationships break for enterprise AI, and what’s needed to deliver accurate, trustworthy AI outputs at scale.
Raw feeds without context create endless rework. This metadata-first blueprint shows how to turn changing source feeds into governed, reusable data products with automated validation, lineage, and GenAI-ready contracts.
Context engineering is the systematic practice of designing and controlling the information AI models consume at runtime, ensuring outputs are accurate, auditable, and compliant.
AI is shifting data engineering from code-heavy ETL to prompt-driven pipelines. Explore where LLMs fit, common pitfalls, and how Nexla makes AI-ready data workflows practical.
Learn how to transform your data into AI-ready assets. Understand the components of AI-ready data and how Nexla’s data product capabilities empower your AI initiatives.
At the 2025 Data + AI Integration Summit, a conversation between Amey Desai (CTO at Nexla) and Qingyun Wu (Founder & CEO at AG2) unpacked how multi-agent systems and orchestration frameworks are shaping the next generation of enterprise AI.
Success now hinges on how well businesses share data beyond their walls. Seamless intercompany data flow fuels smarter decisions, faster collaboration, and real growth. In this new era, connection is the key to competitiveness.
Success now hinges on how well businesses share data beyond their walls. Seamless intercompany data flow fuels smarter decisions, faster collaboration, and real growth. In this new era, connection is the key to competitiveness.
