Query IntelligenceAt Your Fingertips
The AI data processor to query intelligence at scale. Transform unstructured data into business-ready insights.
Introducing the AI data processor
Run prompts as queries over large amounts of data. Get structured outputs you can trust. Powered by a new distributed computing architecture for AI data processing that is purpose-built to query intelligence on demand and in real time.
DataData
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| 10234 | I've been waiting for 2 hours and still haven't gotten help. This is unacceptable! |
| 10235 | Thank you so much for your help! This solved my problem perfectly. |
| 10236 | I'm still experiencing the same error after following all your instructions. Nothing has changed. |
| 10237 | Perfect! The new update fixed everything. I really appreciate the quick response! |
| 10238 | The problem keeps happening. I don't think this workaround is going to cut it. |
Structured Columnar Outputs
AI that understands your target output schema and generates consistent, schema-compliant results ready to plug directly into analytics and BI workflows.
Cost-effective Scalability
AI that runs on our distributed continuous batching architecture, optimized for high throughput and efficient resource utilization, enabling cost-effective processing of large-scale data.
Data Source Agnostic
AI that runs where your data lives. Connect to any data source and start processing on demand and in real time.
Powered by Queryboost-4B
Our 4B model achieves best-in-class structured output accuracy within its weight class, outperforming leading 4B and even 14B open-weight models on reading comprehension and natural language inference benchmarks.
Benchmark Details: Structured output accuracy measures the percentage of model outputs that both conform to a predefined JSON schema and contain the correct answer. Each benchmark (HellaSwag, MultiNLI, RACE, BoolQ, SQuAD 2.0) was adapted for schema-constrained decoding evaluation, requiring the model to produce structured JSON outputs instead of free-form text. Results represent zero-shot performance. HellaSwag measures commonsense reasoning, MultiNLI tests natural language inference, RACE evaluates reading comprehension, BoolQ assesses yes/no question answering, and SQuAD 2.0 measures question answering with unanswerable questions.
Model Description: Queryboost-4B was post-trained for data processing, schema awareness, and structured output generation.