Unstructured text data is generated across every part of an organization, from sales reports and customer interactions to support tickets and employee evaluations. Yet most of it remains unstructured and untapped. dotData TextSense extracts “semantic labels” from text and connects them with your business data to reveal meaningful insights that directly impact performance. Identify early signs of customer dissatisfaction or churn, uncover success patterns in sales reports, or detect morale risks from one-on-one meeting notes. dotData TextSense helps you analyze text data and turn it into concrete business actions.
dotData TextSense
Beyond Text Mining with AI-Powered
Text Analysis Software
Automatically unlock valuable insights from text data in just a few minutes without any pre-processing or expert setup.
Turn Untapped Text into Your Growth Engine
AI Text Analysis Tool for Everyone
Traditional text analytics tools require time-consuming steps, including dictionary preparation, morphological analysis, and manual tuning of parameters, which makes the process more complicated and costly. Even more advanced natural language processing tools often fail to understand context, interpreting phrases like “I was unable to visit customers” as simply “visit” and “customer.” dotData TextSense leverages generative AI to accurately understand nuance and intent without requiring complex pre-processing or linguistic expertise. It enables intuitive and accessible text analytics for everyone, truly democratizing text analysis.
AI-Powered Label Recommendation and
Automatic Prompt Optimization
dotData TextSense ensures continuous high accuracy through two AI capabilities. First, it automatically recommends semantic labels to extract from textual data, such as “delivery delays,” “pricing complaints,” or “UI confusion.” Users can simply select from the suggested labels to begin analysis. Next, the system automatically adjusts its prompts based on correct labels supplied by users, improving coverage and precision over time without the need for manual prompt engineering.
Key Features
dotData TextSense transforms unstructured text into structured, actionable data through semantic labeling. With a user-friendly interface and automated AI capabilities, even non-technical users can perform advanced analytics and gain key insights quickly and efficiently without data scientist expertise.
Analyze Without Complex
Pre-processing
Tokenization, stopword filtering, and synonym dictionary setup are no longer necessary. dotData TextSense utilizes generative AI to interpret text directly, reducing preparation time and costs while eliminating the need for specialists. Empower business users to take the lead in analysis and get actionable insights in just a few clicks.
AI-Recommended
Semantic Labels
AI automatically analyzes text and proposes semantic labels such as “Missing reproduction steps” or “Known issue” for support logs, “Price dissatisfaction” or “Delivery delay” for VOC data, and “Burnout signs” for HR records. Choose from the suggested labels to start. Reduce manual tagging, ensure consistency, and expand analytical ideas.
AI-Adjusted Prompts Through Feedback Loops
Improve accuracy through simple feedback. Mark results as correct or incorrect, and the AI automatically refines its prompts. It adapts to negations, paraphrases, and industry-specific expressions without requiring prompt design or manual tuning. Each iteration increases precision and stability.
Analyze Text Across
Industries
From manufacturing maintenance records and sales reports to customer feedback, support tickets, incident reports, and HR logs, dotData TextSense helps you structure and analyze text across industries and departments. Quickly move from visualizing data to analyzing root causes and making predictions.
Combine Structured and Unstructured Data for Deeper Insights
One of the key features of dotData TextSense is seamless integration of its semantic labels with dotData Insight or dotData Feature Factory. Combining structured and unstructured data reveals the underlying drivers of outcomes, thereby improving decision-making accuracy.
Reduce Generative AI Costs by up to 90 Percent
Through sampling, shared prompts, caching, and mini-batch optimization, dotData TextSense can reduce generative AI costs by up to 90 percent compared to conventional approaches.
This allows cost-effective scalability from prototype design to full-scale deployment.
Steps to Use
Get Ready in Seconds with Drag and Drop
- Prepare your text data, such as sales reports or even social media data, in CSV format with one text entry per row.
- No preprocessing or dictionaries are required. Drag and drop the file into the intuitive interface to get started.
Automatic Label Suggestions Based on Context Understanding
- AI analyzes the context of your text and automatically suggests relevant semantic labels.
- This eliminates the need for manual label design and ensures objective, comprehensive coverage.
You can also create custom labels directly in the interface.
Improve Accuracy Effortlessly Through Feedback
- Provide simple feedback on AI-generated labels.
- dotData TextSense interprets your feedback and automatically adjusts prompts to improve precision without requiring prompt engineering or specialized knowledge.
Download and Use Immediately as Structured Data
- Once the prompts are optimized, dotData TextSense labels all text data and converts it into structured form.
- You can download the labeled dataset and immediately use it for visualization, trend analysis, or predictive modeling.
What Our Customers Say
Exeter Finance
The biggest problem is that, when doing it manually, it’s just a repetitive, trial-and-error process that takes time. dotData solves a problem I’ve been trying to solve for 20 years.
sticky.io
I was spending 95% of my time wrangling data…now I can offload most of that work and just focus on delivering viable patterns and insights.
Use Cases
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dotData's AI Platform Maximize Data Utilization through Feature Discovery
dotData leverages automated feature engineering to build models using machine learning, enhancing data by accumulating feature values as assets and extracting valuable insights, enabling businesses to become more data-driven. Our platform satisfies a wide range of needs, including business transformation, and support the effective use of data and AI to drive innovation and growth.
Request a Demo
We offer support tailored to your needs, whether you want to see a demo or learn more about use cases. Please feel free to contact us.
Frequently Asked Questions
Conventional text analysis tools rely on word frequency and pre-prepared dictionaries for analysis, and use techniques such as word clouds and keyword density to interpret the analysis results indirectly. This limits the ability to understand context and interpret negative sentiment. Meanwhile, dotData TextSense utilizes large-scale language models to directly capture the meaning and intent of the entire sentence and extract them as “semantic labels.” This makes it significantly different from conventional methods in that it allows anyone to achieve highly accurate and interpretable text analysis, which was difficult to achieve with conventional methods.
dotData TextSense can analyze a large volume of text from various data sources, such as sales reports, to identify factors that lead to successful sales, or systematically organize survey responses to improve customer satisfaction. While traditional text analytical tools require significant time and effort to perform sentiment analysis, dotData TextSense semantically labels social media and review data, making customer sentiment analysis easier and faster. Regardless of industry, including retail, finance, manufacturing, and IT, dotData TextSense can be used in a wide range of applications to discover new insights and improve the quality of decision-making by combining unstructured text with business data.
Using generative AI for text analysis, security is the top priority. dotData TextSense supports multiple APIs, including OpenAI, Azure OpenAI, Amazon Bedrock, and vLLM, allowing users to select the API they are authorized to use. The second concern is cost. The more unstructured data a text mining process handles, the higher the cost of running generative AI becomes. dotData TextSense performs fast, low-cost verification using downsampling during the label design and evaluation stages, and reduces inference tokens by using batch APIs, prompt optimization, and caching when labeling all data, reducing costs by up to 1/10.
AI text analytics is a technology that uses AI to analyze large data volumes and extract actionable insights automatically. While conventional text analysis tools require dictionary development, data cleaning, and processing, AI text analytics tools use natural language processing to understand context and sentiment and perform quantitative text analysis. This technology can be used to understand changes in customer satisfaction, obtain hints to turn customer feedback into insights to improve products and services, and improve the accuracy of analysis results in the decision-making process. dotData TextSense is designed to make these AI text analysis techniques easy for anyone to use, helping streamline data analysis and result interpretation.
