Transceve offers a generative AI platform that analyzes unstructured conversation data from sources like call transcripts and chat logs. It extracts both quantitative metrics and qualitative narratives to help social purpose organizations measure and report on their impact in near real-time.
Funding
Funding not disclosed
Founders
Product
Problem
Social purpose organizations struggle to quantify and report on their impact due to reliance on outdated feedback mechanisms and the challenge of analyzing unstructured conversational data. This results in significant time expenditure on manual data aggregation and a lack of real-time, actionable insights into service effectiveness.
Solution
Transceve provides a generative AI-powered analytics platform that processes unstructured conversation data from various sources, including call transcripts, chat logs, and case notes. The platform extracts both measurable quantitative data and qualitative narrative insights, enabling organizations to understand their impact in near real-time. By transforming raw conversations into actionable intelligence, Transceve eliminates the need for traditional feedback forms and manual reporting processes. This allows social purpose organizations to more effectively demonstrate their social value and make data-driven decisions to improve their services.
Target Audience
The primary customers are social purpose organizations, including charities and non-profits, that need to measure, report on, and improve their social impact.
Features
- Generative AI engine for natural language processing of unstructured conversation data
- Extraction of quantifiable "number data" for impact measurement and reporting
- Identification and compilation of compelling "story data" for qualitative impact demonstration
- Integration capabilities with diverse data sources such as call transcripts, chat logs, and case notes
- Near real-time analysis and insight generation
- Prompt engineering approach to mitigate inherent biases in Large Language Models, with explicit instructions for equality, diversity, and inclusion
- Optimized model usage for environmental efficiency