smartR AI enables teams to analyze unstructured free-text data from forms, surveys, incident reports, and customer feedback using SCOTi AI. This helps organizations classify responses automatically, identify trends, and uncover hidden patterns without manual tagging or predefined rules.

Business challenge

Organizations collect large volumes of valuable unstructured text, but extracting insights from free-text fields is labor-intensive, inconsistent, and costly. Traditional approaches such as keyword searches and manual tagging are slow, error-prone, and too inflexible for new questions or emerging issues.

Solution

SCOTi AI’s Free-Text Classification lets users analyze unstructured text by asking natural-language questions. The platform dynamically categorizes responses, identifies trends, and surfaces hidden patterns, making free-text data searchable and actionable at scale.

Key capabilities

Automated free-text classification
Classifies unstructured text automatically without manual tagging or predefined rules.

Natural-language querying
Lets users ask plain-English questions and get structured answers from free-text datasets.

Trend and pattern detection
Identifies root causes, trends, and risks hidden in comments, narratives, and descriptions.

Scalable analysis
Processes millions of records in seconds and works on historical or real-time data.

Privacy-first deployment
Supports on-premise or private cloud deployment so data stays within the organization.

Multi-source integration
Works with CRMs, ERPs, databases, and spreadsheets.

Results

Cost savings by processing 1M+ records for under $0.65 versus thousands in labor costs.
Speed and efficiency with analysis of millions of records in seconds.
Adaptability to answer new questions on demand without re-tagging data.
Actionable insights that uncover buried trends, root causes, and risks.
SCOTi is also described as 1000x faster than manual analysis and capable of proactive risk mitigation.

Industry best fit

Healthcare, retail, manufacturing, insurance, HR, logistics, and other organizations that rely on large volumes of free-text data for operational insight, trend monitoring, and faster decision-making. The healthcare symptom trend example and cross-industry sample questions are shown in the PDF.