Jabs provides an AI‑powered platform that automatically ingests unstructured text from sources like emails, chat logs, surveys, and social media, then applies natural language processing to extract sentiment, entities, and topics. The extracted insights are delivered in real‑time through customizable dashboards, alerts, and APIs that integrate with existing CRM, ticketing, and BI tools, enabling enterprises to quickly identify issues, trends, and opportunities.
Funding
Funding not disclosed
Founders
Product
Problem
Jabs addresses the difficulty organizations face in efficiently collecting, analyzing, and acting on large volumes of unstructured textual data from sources such as customer feedback, support tickets, and social media.
Solution
Jabs offers an AI-powered platform that automatically ingests unstructured text, applies natural language processing to extract key insights, and presents the results in customizable dashboards. The system uses large language models to perform sentiment analysis, topic clustering, and trend detection, enabling users to quickly identify emerging issues and opportunities. Integrated APIs allow seamless connection to existing data pipelines, while role-based access controls ensure secure collaboration across teams. By delivering actionable intelligence in near real-time, Jabs helps businesses improve decision‑making, reduce response times, and enhance customer experience.
Target Audience
Primary customers are mid‑size to large enterprises in customer support, product management, and marketing that need to derive insights from high‑volume textual feedback.
Features
- Automated ingestion of text from emails, chat logs, surveys, and social media feeds
- NLP engine with sentiment scoring, entity extraction, and dynamic topic modeling
- Real‑time trend monitoring and anomaly alerts configurable per business rule
- Interactive dashboards with drill‑down visualizations and export options
- RESTful and webhook APIs for integration with CRM, ticketing, and BI tools
- Role‑based permissions and audit logging for secure multi‑user collaboration