The Context Modern businesses store their most valuable information across a fragmented landscape of live databases (like MongoDB and PostgreSQL) and cloud spreadsheets (like Google Sheets). This data is the lifeblood of decision-making, yet it remains locked behind technical barriers.
The Problem Currently, extracting insights from live data requires either advanced SQL knowledge or the constant assistance of data engineering teams. Non-technical users, such as product managers, founders, and analysts are forced to rely on static exports, stale reports, or complex BI tools that require weeks of setup. This creates a "data bottleneck" where the people who need answers the most cannot access them in real-time.
The Solution: Wup Wup bridges this gap by providing a zero-code, natural language interface for live data. By securely connecting to multiple data sources simultaneously, Wup allows users to "talk to their data" as if they were chatting with a teammate.
| Metric | Measured By | Objective | Target |
|---|---|---|---|
| Retrieval Relevance | Context Precision | Find the exact data in PDFs | > 92% accuracy |
| End-to-End Latency | Time to First TokenM | Minimize wait time for users | < 2.0 seconds |
| Tool Success Rate | Execution Reliability | Successful live DB connections | 99.9% uptime |
| Groundedness | Faithfulness Score | Eliminate AI "hallucinations” | 100% cited answers |
| Data Integrity | Summary Accuracy | AI math matches actual DB records | 1:1 mathematical parity |
| Transcription Quality | BLEU / WER | Accurate text-to-query conversion | Minimal data loss |