Powering Enterprise AI With SingleStore

You’ve probably asked yourself:

“How can I streamline this work and choose an architecture that’s flexible? And how do I ensure my data stays safe and doesn't end up where it shouldn’t?”

With enterprise AI, simplicity and security are everything.

Well, you know what is simple and secure? A single, unified platform that can transact, analyze and search all your data in a single place.

You know what's not simple and secure? Cobbling together a patchwork assortment of legacy architectures that were never intended for real-time AI. Relying on a grab bag of databases, vector stores, analytics engines and a model-serving infrastructure only serves to slow down the AI, drive up costs and limit innovation.

The answer lies in distilling your data to a single platform, and only SingleStore has the all-around performance to be that one platform.

Think of a decathlon, where winning requires well-rounded athletes who are exceptional at every sport. That’s the kind of versatility that SingleStore brings to the table — with the performance to handle everything from fast reads and writes required by today’s modern apps to more complex tasks like vector and full-text search, relational and JSON analytics, GPU-accelerated processing and more. By contrast, our competitors can manage only a fraction of these features with reasonable price and performance.

SingleStore can do this because we are natively engineered to have enough performance to make single-shot retrieval possible.  What does that mean? The easiest way to explain is to first describe what it isn't.

Not single-shot retrieval

Look at all those disparate data sources; not simple, not secure — and retrieval results in the agent navigating a maze of unnecessary handoffs and conversions.   

But let's be honest: when you built your app, you probably didn’t think about integrating all those data sources, because that kind of integration is too hard and time intensive. Instead (and like most organizations), you likely picked one for the initial prototype. When you pick and choose, though, something inevitably gets lost in translation. In this scenario, your agent only has partial context, which can lead to hallucinations. So while your chosen route may be simple and secure, all you’ve really created is an agent that’s not very smart — defeating the purpose of AI.  

SingleStore, on the other hand, has the all-around performance you need for enterprise AI workloads, so you don't need to stitch together multiple databases and can do everything in just one shot. That’s the meaning of single-shot retrieval.

Single-shot retrieval

With single-shot retrieval the agent composes a comprehensive query that executes a sequence of steps with automatic hierarchy of processing and executing to retrieve the relevant context in one go in the simplest use case. You can fine tune and break this query to further squeeze the performance per your business needs — and we make it as simple as possible.

With single-shot retrieval your agent is simple, secure and smart because it has all the context it needs to do its best work within sub-seconds. You no longer have to wait for it to fetch all the information from different data sources across different interfaces.

This single-shot retrieval capability is just one aspect of SingleStore's comprehensive enterprise AI platform. Here's how our core capabilities work together to deliver unmatched performance for your AI applications:

1. Process live, dynamic data at scale with SingleStore's streaming ingestion capabilities that handle millions of events per second with lock-free parallel ingestion.
2. End batch processing delays with SingleStore's Universal Storage format that brings together the fast table scan performance of a columnstore and the selective seek performance of rowstore indexes, allowing you to run complex analytics on fresh operational data without ETL.
3. SingleStore offers integrations with leading tools like OpenAI, Hugging Face, LangChain and LlamaIndex, making it easy to build sophisticated AI applications including Retrieval-Augmented Generation (RAG) pipelines and knowledge graph implementations.
4. Simplify data ingestion from multiple sources with SingleStore's intuitive interfaces that minimize the learning curve for new users. Tools like SingleStore Notebooks allow developers to quickly prototype applications and workflows without extensive database expertise.
5. Deploy and serve LLMs with SingleStore's Aura Container Service, which provides GPU support for optimal model performance. This allows you to keep AI processing close to your data, minimizing latency and maximizing security.

This is only possible on SingleStore, because only SingleStore delivers the performance you need for enterprise AI. It can hold and index almost any kind of data being multimodal — and that also means you can push the boundaries of what you can achieve with your AI workloads, with minimum investment in learning and integrating every new data platform that comes to the market.

Start free with SingleStore.