Transform Your Data Into

Intelligent Insights

Deploy AI-powered Data Agents that understand, analyze, and act on your data autonomously. No coding required, instant insights delivered.

Works with any data lake

DATA AGENT ARCHITECTURE

Data Catalog

Centralized metadata management with data lineage tracking, governance, and easy discovery of all your data assets.

Data Center

Central hub managing data from multiple sources with native connectors and micro-functions for automated actions.

AI Data Agents

Autonomous virtual analysts that process, analyze, and interpret data using advanced Agentic AI and pre-configured LLMs.

DATA AGENT SUPPORTS

Databricks

Snowflake

Azure

AWS Athena

Google Cloud

PostgreSQL

MongoDB

JDBC

Intelligent Features That Transform Data Work

Natural Language Interaction

Ask complex data questions in plain English. Our AI agents understand your intent and deliver precise insights instantly.

Autonomous Analysis (Agentic AI)

AI agents proactively monitor data, identify patterns, and flag anomalies without explicit prompts, acting independently.

No-Code Agent Building

Build and deploy powerful data agents using our intuitive visual interface. No technical expertise required.

Document Intelligence

Process unstructured documents like PDFs and text files to extract precise answers and valuable insights automatically.

AI-Powered KPI Suggestions

Accelerate setup with intelligent recommendations for key performance indicators derived from your data sources.

Actionable Recommendations

Beyond insights, agents identify and propose concrete actions, leveraging micro-functions to trigger workflows based on analysis.

Feature/Capability	Structured Data Processing	Unstructured Data Processing (Large Document Collections)
Data Sources	Databases (SQL, NoSQL), APIs, Flat Files (e.g., CSV, Excel)	Documents (PDFs, Text Files), Web Content, Communication Logs (Emails, Chat), Audio Transcripts, Images (Metadata)
Primary Processing Focus	Quantitative Analysis, Aggregation, Relational Queries, Numerical Pattern Recognition, Statistical Modelling	Natural Language Understanding, Semantic Analysis, Contextual Interpretation, Information Extraction, Sentiment Analysis, Thematic Grouping
Key Techniques/AI Components	Traditional BI/Analytics, Machine Learning Models (for prediction/classification), AI-Powered KPI Suggestions, Pre-defined "Micro Functions" (Tool Use)	Large Language Models (LLMs), Agentic AI, Semantic Embeddings, Knowledge Graph Algorithms, Natural Language Processing (NLP)
Typical Outputs/Insights	Key Performance Indicators (KPIs), Interactive Dashboards, Predictive Models, Anomaly Alerts (Numerical), Actionable Workflow Triggers, Financial Reports, Sales Forecasts	Extracted Entities & Relationships, Knowledge Graphs, Semantic Search Results, Summaries (Abstractive/Extractive), Sentiment Analysis, Thematic Trends, Multi-Document Synthesis, Due Diligence Reports, Competitive Intelligence
Core Value Proposition	Precision, Efficiency in Quantitative Analysis, Operational Optimization, Performance Monitoring, Data-Driven Forecasting	Deep Contextual Understanding, Unlocking Hidden Information, Cross-Document Reasoning, Enhanced Discovery, Risk Identification (Textual), Qualitative Analysis at Scale
Example Use Cases	Sales Forecasting, Financial Reporting, Supply Chain Optimization, Customer Churn Prediction, Inventory Management	Legal Document Review, Research Synthesis, Contract Analysis, Customer Feedback Analysis, Fraud Investigation (Textual), Compliance Monitoring, Market Research

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