Decodable

As Eric Kavanagh put it in our Predictions for 2025 tech talk, we are at an incredible moment of transformation: a double inflection point for streaming and AI. While AI often grabs the spotlight, Eric makes a bold prediction: by 2025, streaming will have a greater impact. Why? ? Streaming is more mature. ? Its use cases are clear and transformative. ? A greenfield streaming architecture is like "Valhalla to the Vikings"—a once-in-a-lifetime opportunity to solve problems and unlock innovation. ?? Ready to explore why streaming might outshine AI in the coming years? Don’t miss the on-demand replay of this insightful session ?? https://dcdbl.co/3ZGZSth

Discover how Medidata reduced latency, enabling their data consumers to access critical insights in minutes. Watch the on-demand tech talk for the full story ?? https://dcdbl.co/4gDouJX

At their core, agentic AI systems go beyond passive responses and exhibit autonomous decision making, goal setting, and self-improvement. Agentic AI functions by continuously ingesting real-time data, understanding context through memory and vector databases, and autonomously planning and executing tasks. It processes complex objectives by breaking them down into actionable steps, prioritizing decisions based on dynamic inputs, and interacting with systems or users to achieve its goals. Through reinforcement learning and feedback loops, it continuously adapts and refines its strategies, improving over time. This adaptability allows agentic AI to operate with greater efficiency and effectiveness in dynamic environments. Agentic AI workflows require a continuous flow of fresh, operational data to keep vector databases updated, augment user prompts to LLMs with real-time context, and ensure AI outputs remain current and accurate. Decodable simplifies this process by enabling continuous data ingestion from heterogenous sources like CRM, OLTP, and OLAP systems, ensuring that LLMs always have access to the most up-to-date context. By efficiently chunking, embedding, and ingesting into vector stores, AI agents are continuously provided with fresh insights to drive smarter, more informed decisions. By facilitating seamless real-time updates, Decodable eliminates batch latency, allowing AI interactions to remain truly adaptive and responsive to evolving data. Learn more ?? https://dcdbl.co/43oRh1C

Building enterprise AI requires more than just access to large language models (LLMs). To generate accurate, context-aware responses, AI needs access to fresh, real-time data while maintaining security and compliance. Today, we’re excited to announce how Decodable and Vellum are enabling enterprises like Drata to build secure, high-performance AI systems powered by real-time data streaming. With Decodable’s real-time streaming infrastructure and Vellum's collaborative platform for building production-grade AI solutions, enterprises can roll out agentic AI faster than ever. By enabling AI to dynamically retrieve, process, and generate insights in milliseconds, Decodable and Vellum help teams go from concept to production at speed—without compromising intelligence or security. Decodable seamlessly integrates with data sources to ingest, continuously build the context, and deliver to vector databases, ensuring AI systems operate on the freshest possible data. Powered by Change Data Capture (CDC) and Apache Flink, Decodable delivers: ? Real-time Pipelines - Ensure that vector databases receive continuous data updates from production pipelines, ensuring more correct or useful results in real-time. ? Contextual Relevance - Connect disparate inputs, providing AI with deep, rich, fresh context to improve decisions, responses, and actions. ? Scalability and Flexibility - Integrate data sources, sinks and formats through a rich data connector library. Decodable also simplifies processing high-volume data sources like clickstream or transactional data to create reliable, production data pipelines at scale. Vellum enables rapid prototyping, testing, and deployment of reliable AI solutions. With Vellum's purpose-built GUI and SDK, enterprises can: ?? Validate retrieval strategies before indexing data into vector stores. ?? Monitor and govern AI outputs to ensure compliance and security. ?? Iterate on AI features faster, optimizing performance for real-time use cases. Learn more ?? https://dcdbl.co/41I5dTf

Decodable’s real-time data platform used to be “always-on” to ensure low-latency data processing. But we understand that not every workload demands constant processing. Many of our customers deal with sporadic or batch-based event sources, making it inefficient to keep jobs running idly. The result? Wasted resources and unnecessary costs. Our new Scale to Zero feature solves this challenge by empowering teams to automatically pause jobs during idle periods and resume them later, thereby providing a seamless, efficient, and cost-effective streaming experience. Scale to Zero introduces intelligent job lifecycle management with automatic pausing based on user-defined and system conditions, as well as automatic resuming so that paused jobs can resume based on a configurable trigger—this ensures your jobs reactivate promptly to process fresh events. Scale to Zero is available now. Whether your workloads are event-driven or batch-oriented, this feature empowers you to optimize costs while maintaining the responsiveness of your data pipelines. https://dcdbl.co/4gXxoBZ

The most complete solutions for real-time data are provided by those who can offer a fully managed platform, one that integrates all the necessary components so that your stream processing jobs just work. In addition to Flink as the base layer, they provide the observability that production environments demand, the security features that protect your data, and the controls you need to run your workloads efficiently - all without burdening you with internal configuration settings that need endless fine-tuning to keep the platform running smoothly. At this level, the focus is on implementing your business logic, whether that’s in SQL, Java, or Python. No pre-existing Flink knowledge is assumed or required, although it should be your choice. (If you have Flink JAR files you need to run, that needs to be fully supported.) If you’d prefer to use SQL, you don’t have to write any Java code. The developer experience also includes a web UI, a robust CLI tool, a dbt adapter, and a unified set of APIs for the entire platform so that it works seamlessly within your established ecosystem. Decodable offers a simplified, unified approach to real-time data with a fully managed, serverless platform that eliminates the complexity and overhead of managing infrastructure. It allows data engineering teams to focus on building pipelines using SQL, Java, or Python. With a wide range of connectors for seamless data movement between systems and powerful stream processing capabilities, Decodable enables developing real-time pipelines with ease. The platform ensures operational reliability through built-in security, compliance, and a dedicated support team that acts as the first line of defense for your data pipelines. https://dcdbl.co/41u9qdh

Medidata leverages Decodable to continuously cleanse, transform, and format the data in Iceberg to provide gold-level data sets in real-time at scale. Watch the on-demand tech talk for the full story ?? https://dcdbl.co/4gDouJX

In today’s AI-driven environment, companies are transforming how they process data to gain competitive advantages, capture new revenue opportunities, and reduce risk. While key technologies enable this transformation, they also introduce complexities in deriving intelligence from real-time data streams. We hope you can join us at the Gartner Data & Analytics Summit for our session where we will share insights from Fidelity Investments' journey in building an event streaming platform, highlighting strategies and lessons learned to empower organizations to stay ahead in the evolving data landscape. Be sure to stop by for a quick demo and a chance to talk to our team of experts--you'll find us in the Data Management Tools & Technology hub at Booth #830. #GartnerDA https://dcdbl.co/43hWoAH

Putting the final touches on our booth for the Gartner Data & Analytics Summit! Who else is going? #GartnerDA

In today’s AI-driven environment, companies are transforming how they process data to gain competitive advantages, capture new revenue opportunities, and reduce risk. While key technologies enable this transformation, they also introduce complexities in deriving intelligence from real-time data streams. We hope you can join us at the Gartner Data & Analytics Summit for our session where we will share insights from Fidelity Investments' journey in building an event streaming platform, highlighting strategies and lessons learned to empower organizations to stay ahead in the evolving data landscape. Be sure to stop by for a quick demo and a chance to talk to our team of experts--you'll find us in the Data Management Tools & Technology hub at Booth #830. #GartnerDA https://dcdbl.co/43hWoAH