DeepResearch is not designed to handle real-time information or provide results based on very recent web data. Its architecture prioritizes processing pre-indexed datasets and structured information from known sources, which limits its ability to reflect live updates. The system typically operates on snapshots of data collected during periodic crawls, meaning its results are only as current as the last update cycle. For most use cases, this delay ranges from hours to days, depending on the data source and how frequently DeepResearch refreshes its indexes. Developers should treat it as a tool for analyzing historical or semi-recent information rather than live events.
The update frequency varies by data type. For example, news articles might be refreshed daily, while academic publications or technical documentation could be updated weekly or monthly. DeepResearch uses scheduled crawlers and APIs to pull data from sources like government databases, research repositories, and news aggregators. These integrations often include built-in rate limits or caching mechanisms to avoid overloading third-party services, which introduces additional latency. If a source updates its content at 3 PM, DeepResearch might not ingest those changes until its next scheduled crawl—say, midnight. This approach balances freshness with system stability but makes it unsuitable for monitoring rapidly changing scenarios like stock prices or social media trends.
Developers needing near-real-time data can extend DeepResearch by integrating live APIs or streaming services alongside it. For instance, pairing it with a WebSocket feed for financial data or a live news API could supplement its static datasets. However, this requires custom code to merge real-time and historical data streams. DeepResearch’s core strength lies in structured analysis of established information, such as identifying trends in academic papers or comparing product reviews over months. If your project demands minute-by-minute accuracy, consider combining it with specialized real-time systems rather than relying on it alone. Always verify the timestamps of its source data through its API or metadata endpoints to gauge recency.