Orangespark provides an AI‑powered platform that automatically ingests, processes, and structures large volumes of unstructured text such as documents, emails, and support tickets. Using fine‑tuned large language models, it extracts entities, sentiment, dates and topics, and delivers searchable, categorized outputs via a web UI or REST API, with real‑time alerts and dashboards for regulated enterprises and customer‑support teams.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations need to extract actionable insights from large volumes of unstructured text data, but manual analysis is time‑consuming, error‑prone, and requires specialized expertise.
Solution
Orangespark offers an AI‑powered platform that automatically processes, summarizes, and categorizes textual content such as documents, emails, and support tickets. The system leverages large language models combined with custom pipelines to identify key entities, sentiment, and topics, delivering structured outputs that can be integrated into existing workflows. Users can query the processed data through a web interface or API, enabling rapid retrieval of relevant information without manual review. The platform also provides configurable alerts and dashboards to monitor trends and anomalies in real time.
Features
- Automated ingestion and preprocessing of diverse text formats (PDF, DOCX, email, chat logs)
- Summarization and extraction of entities, dates, and sentiment using fine‑tuned large language models
- Customizable taxonomy and tagging rules for domain‑specific classification
- RESTful API and web UI for querying processed data and generating reports
- Real‑time alerting and visual dashboards for trend monitoring
- Secure, GDPR‑compliant data handling with end‑to‑end encryption