Palo provides a no‑code AI platform that ingests and analyzes multi‑modal unstructured data—text, images, audio, and video—to produce structured outputs such as entity extraction, sentiment scores, and visual classifications. Users can build drag‑and‑drop pipelines with pre‑trained or custom models, integrate results via APIs, and collaborate on annotations, reducing the need for specialized data‑science resources.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations need to extract actionable insights from large volumes of unstructured data such as text, images, and video, but existing tools require extensive manual labeling, domain expertise, and integration effort, limiting scalability and speed of decision‑making.
Solution
Palo offers an AI‑powered platform that automates the ingestion, annotation, and analysis of unstructured data across multiple modalities. Users can upload raw data, apply pre‑built or custom models, and receive structured outputs—including entity extraction, sentiment scores, and visual classifications—without writing code. The platform provides a visual workflow builder for configuring pipelines, integrates with common data storage and analytics tools via APIs, and supports collaborative review to refine model performance. By centralizing data processing and delivering ready‑to‑use insights, Palo enables businesses to accelerate analytics projects and reduce reliance on specialized data science resources.
Target Audience
Primary customers are enterprises and mid‑size companies in sectors like finance, healthcare, and media that need to process large volumes of unstructured content for analytics, compliance, or operational automation.
Features
- Multi‑modal data ingestion supporting text, images, audio, and video files
- No‑code pipeline designer with drag‑and‑drop components for preprocessing, model inference, and post‑processing
- Library of pre‑trained models for common tasks such as OCR, entity recognition, sentiment analysis, and object detection
- API and SDK integrations for seamless connection to data lakes, BI platforms, and custom applications
- Collaborative annotation workspace with version control and role‑based access
- Automated model selection and hyperparameter tuning to optimize performance on user data