Findly is an advanced AI analytics tool designed to simplify data management and reporting. It integrates seamlessly with popular platforms, enabling users to query their databases using natural language. This AI-powered solution transforms raw data into meaningful insights, making it easy to visualize and understand complex datasets. Whether in sales, marketing, or inventory management, Findly provides businesses with the information they need to make informed decisions quickly and efficiently.

Klavis.ai is an enterprise-grade AI observability agent that unifies logs, metrics, traces, and events into a single AI-driven layer. It supports connectors for Prometheus, Elastic, Grafana, AWS CloudWatch and more. Teams can ask natural-language questions about system health, receive instant anomaly alerts, and get guided remediation steps. Its AI models correlate data across services to pinpoint failures, reduce alert noise, and proactively surface performance issues before they impact users.

PandasAI is an innovative Python library that integrates generative artificial intelligence capabilities with pandas dataframes. By making dataframes conversational, users can now ask questions and get answers in natural language, streamlining the data analysis and visualization process. The library supports various tasks such as data cleaning, data summarization, and feature generation, thereby providing an efficient and user-friendly approach to managing data.

PixelTable Agent is a web-based AI assistant designed to streamline spreadsheet data analysis. After uploading your dataset or syncing with cloud storage, you can interact with your data through a conversational interface. Ask for summaries, specific metrics, or pattern detections, and PixelTable Agent will automatically generate pivot tables, charts, and formula suggestions. It supports data cleaning tasks like deduplication and outlier detection, and you can export results in various formats. With built-in collaboration features, teams can share insights and reports seamlessly. By automating repetitive analysis steps, it reduces manual errors and accelerates decision-making, catering to both technical and non-technical users seeking a more intuitive and efficient way to work with data.