Secure, Conversational

Terno — Your AI Data Scientist

Unlock fast, accurate insights on your data. Let AI handle the complexity so teams can focus on decisions. Built for enterprise security, multi-database workflows, and production-ready automation.

What is Terno AI?

Terno AI is an advanced AI Data Scientist platform that transforms how organizations interact with their data. It combines agentic reasoning, a virtual semantic database layer, enterprise-grade security, a Python sandbox, and a memory-driven analytics engine — all accessible through natural language.

Businesses use Terno AI to query databases, run analytics, clean and visualize data, build ML models, generate reports, and automate workflows using simple English instructions.

Key Features

Deployment Flexibility

Web, Desktop, AWS, On-Prem

Run Terno as a Web App, Desktop App, AWS AMI, or fully on-premises to match enterprise infrastructure needs.

Security & SQLShield

Query Sanitization & RBAC

Prevents unsafe SQL, enforces RBAC, and ensures read-only, masked access so the LLM can never exfiltrate data directly.

Secure Python Sandbox

Safe Execution

Run transformations, EDA, modeling and exports inside an isolated sandbox — Python code executes safely without risking your infra.

Multi-Database Connectivity

Cross-DB Queries

Connect PostgreSQL, MySQL, Snowflake, BigQuery, Databricks, and Oracle simultaneously — including cross-database joins in one conversation.

Memory Layer

Context Retention

Remembers prior interactions to attach examples and reduce LLM token usage while improving precision in analytics workflows.

Prompt Expansion

Reusable Prompt Library

Store prompts with code words for reuse, making repeated workflows faster, standardized, and easier to share across your team.

Semantic DB Layer

Metastore & Semantic Layer

Context-aware table & column understanding, FK inference, schema summarization and a metastore that retains business knowledge to generate accurate SQL.

RAG-Based Retrieval

Relevant Tables & Columns

Retrieves the most relevant tables using vector embeddings to supercharge SQL accuracy and speed up analysis.

Agentic Reasoning

COT Engine & Workflows

Autonomous chain-of-thought agents plan, pick tools, run SQL/Python, self-debug, and convert chats into reusable app-services for production.

Data Analytics, Forecasting & Clustering

EDA & ML

Automatically clean, preprocess, generate exploratory data analysis, forecast trends, cluster customers, and build ML models ready for production.

Interactive Visualizations & Files

Charts & Exports

Create charts, dashboards, and export data in CSV, PDF, HTML, JSON, PPT, and image formats for easy collaboration.

Workflow Automation

Reusable App Services

Convert any chat or process into a reusable Python function with parameters, runnable without invoking the LLM.

Multi-LLM Support

OpenAI, Gemini, Claude, Llama

Connect to your preferred language model or local custom models for natural language analytics and generation.

Customizable Organization Prompts

Tailored Reasoning

Experiment with org-level prompt customizations to personalize Terno’s reasoning and SQL generation for your company’s domain.

My Contributions

Virtual Database Layer: descriptions, FK inference, categorization, schema summarization – core to Terno’s semantic SQL engine.

RAG-Based Table & Column Selection: Designed and improved embedding-based retrieval for precision SQL.

Testing: accuracy and reliability testing across multiple domains.

Agent Behaviour Optimization: experiments improving SQL accuracy, token cost, error recovery.

ERP Domain Specialization: tested manufacturing, inventory, sales datasets.

Datasource Export/Import System: JSON-based migration and onboarding flow.

AWS AMI Packaging: built one-click deployment images.

Forecasting & Clustering: ML workflows for real client projects.

Blogs, Demos & Webinars: educational content and product showcases.

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