Datavolo's blog
What's in Datavolo's blog? Insights and inspiration, case studies and community for AI/ML and Data Engineers. Discover what we are talking about everyday here at Datavolo!
Apache NiFi – designed for extension at scale
AI systems need data all along the spectrum of unstructured, structured, and multi-modal. The protocols by which these diverse types of data are both acquired and delivered are as varied as the data types themselves. At the same time data volumes and latency requirements grow ever stronger which demands solutions which scale down and up first – then out. In other words we need maximum efficiency, we can’t resort to remote procedure calls for every operation, and we need to support hundreds if not thousands of different components or tools in the same virtual machine.
Data Pipeline Observability is Key to Data Quality
In my recent article, What is Observability, I discussed how observability is crucial for understanding complex architectures and their interactions and dependencies between different system components. Data Observability, unlike Software Observability, aims to...
Streamlining Trade Finance Operations: Cleareye.ai Chooses Datavolo
In the ever-evolving landscape of trade finance, digitization and compliance automation are paramount for efficiency and regulatory adherence. Enter Cleareye.ai, a pioneering force in the industry. Their digital workbench, ClearTrade®, revolutionizes trade finance...
Building GenAI enterprise applications with Vectara and Datavolo
The Vectara and Datavolo integration and partnership When building GenAI apps that are meant to give users rich answers to complex questions or act as an AI assistant (chatbot), we often use Retrieval Augmented Generation (RAG) and want to ground the responses on...
Datavolo Announces Over $21M in Funding!
Datavolo Raises Over $21 Million in Funding from General Catalyst and others to Solve Multimodal Data Pipelines for AI Phoenix, AZ, April 2, 2024 – Datavolo, the leader in multimodal data pipelines for AI, announced today that it has raised over $21 million in...
Data Engineering for Advanced RAG: Small-to-Big with Pinecone, LangChain, and Datavolo
Data Engineering for Advanced RAG Datavolo helps data teams build multimodal data pipelines to support their organization’s AI initiatives. Every organization has their own private data that they need to incorporate into their AI apps, and a predominant pattern to do...
Collecting Logs with Apache NiFi and OpenTelemetry
Introduction OpenTelemetry has become a unifying force for software observability, providing a common vocabulary for describing logs, metrics, and traces. With interfaces and instrumentation capabilities in multiple programming languages, OTel presents a compelling...
How custom code can add security risk to enterprise AI projects and LLMs
Data teams are actively delivering new architectures to propel AI innovation at a rapid pace. In this blog, we’ll explore how Datavolo empowers these teams to accelerate while addressing the critical aspects of security, observability, and maintenance for their data...
Fueling your AI Chatbots with Slack
The true power of chatbots is not in how much the large language model (LLM) powering it understands. It’s the ability to provide relevant, organization-specific information to the LLM so that it can provide a natural language interface to vast amounts of data. That...
Datavolo Architecture Viewpoint
The Evolving AI Stack Datavolo is going to play in three layers of the evolving AI stack: data pipelines, orchestration, and observability & governance. The value of any stack is determined by the app layer, as we saw with Windows, iOS, and countless other...
What is Data Observability for AI?
In today's data-driven world, understanding and measuring what is happening within and between disparate IT systems is paramount. Modern distributed application systems utilizing complex architectures with microservices and cloud-based infrastructure require a...
Reducing Observability Costs and Improving Operational Support at Datavolo
Finding the Observability Balance Through our evaluation of observability options at Datavolo, we’ve seen a lot of strong vendors providing real-time dashboards, ML-driven alerting, and every feature our engineers would use to evaluate our services across the three...