The Era of Queryable Intelligence
For decades, querying databases of structured data was how we turned information into insight. The next era will be defined by querying intelligence at scale, using AI as a data processor to reason over unstructured data and extract actionable insights.
Beyond Chat and Agents
So far, use of AI has centered around two types of workloads: chat and agents. Chat systems translate prompts into interactive responses, while agentic systems translate prompts into sequences of actions that produce a final output.
- Chat: turn-based prompt → interactive responses
- Agents: prompt → sequence of actions → final output
But there's a third category that remains underserved: data processing. In this mode, a single prompt doesn't just produce a single answer. The prompt is a query that instructs AI to process data at scale, transforming vast amounts of unstructured information into structured insights.
- Data Processing: prompt → AI processes data at scale → structured insights
The infrastructure required for this third category is fundamentally different. Unlike chat or agentic workloads which prioritize low latency for responsive and sequential interactions, AI data processing focuses on maximizing throughput with continuous batching to run large-scale inference pipelines efficiently.
Intelligence at Scale
Imagine AI that can:
- Read millions of customer service conversations to infer resolution and coach agents on how to improve customer satisfaction in specific scenarios.
- Read millions of legal documents to find precedent and craft arguments that uniquely support your case.
- Read millions of financial documents to detect risk patterns or compliance violations across transactions and explain the business impact.
This is the vision for Queryboost. We have designed a new distributed computing architecture for AI data processing that is purpose-built to query intelligence on demand and in real time. Our mission is to enable every organization in the world to run intelligence directly on their data at scale.
Querying AI in the future will be as natural as running SQL today. This is the era of queryable intelligence.