Achieving High AI Accuracy on Data Tasks​

EasyManage AI achieves high near-100% accuracy on the data tasks such as database querying, joining tables in a database, joining across data sources, database transactions.

• This is possible with EasyManage innovation:
  • The separation of data query planning from execution
  • Enabling SQL-like calling via Tools and APIs
  • Data modeling, table joins to bring relevant data in one shot.
  • Database Transactions
  • Data mesh to consolidate data from multiple sources into one call.

We present to you how EasyManage AI's approach helps you succeed on data solution's enterprise AI reliability.

EasyManage AI Approach​

EasyManage AI's innovative approaches help towards

• Avoiding the accuracy degradation that occurs when AI models need to fire multiple queries and process large amounts of data within context.
• Reduce Context rot
• By-pass maximum Tools limits for LLMs

A note on limitations: While EasyManage AI's approach is designed for efficient AI data analysis and automation. For purely generative tasks the accuracy will be what the underlying LLMs offer.

The separation of data query planning from execution​

• We provision LLMs access to full business domain schema
• LLMs are able to understand business domain schema very well,
  • Then with capability to construct SQL query operands and pass to Tools & API, they are able to accurately retrieve only required data, reducing data context size.

Flexible SQL-like calling via Tools and APIs​

EasyManage enables SQL-like calling via Tools and APIs, which LLMs use very nicely. Please navigate thru AI case studies to see examples.

Data Modeling​

• Queries on table joins to bring relevant data from multiple tables in one shot.
• Configure upto five-table joins via UI with type 1:M or 1:1 on each join.

Database Transactions​

• You can easily implement AI transactions, allow LLMs to store data or Query results via database CRUD calls.
• Incrementally store query-retrieved data to arrive at final consolidations.
• Make available historical data context to LLMs

Data Mesh​

• Data mesh to consolidate data from multiple data sources into one call.

Conclusion​

Get End Result → High AI Accuracy on Data Tasks

Path to AI adoption​

We present to you path to AI adoption and get predictable results with EasyManage AI.

Our solution approach​

Listed below are principles that will work really well across customers:

Discover Opportunities With Proactive Insights​

• Get tailored suggestions on insights, trends and workflows based on your data.
• By giving your table schema and data as context,
  • Ask AI What Insights and Trends Can Get?
  • Ask AI What AI Workflows Can Implement
• Generated queries and workflows
  • The Queries and workflow suggestions will be rich enough to capture the breadth of data, API endpoints usage, and table joining models.

→ Uncover the full potential of your enterprise data

Generate plans for your company and domain​

• By giving your table schema and data as context,

  • Ask for and implement data modeling suggestions
  • Ask for and implement sensitive data protection suggestions

• Narrow down on queries and workflows

  • Shortlist Queries generated
  • Get workflow implementation guide, priority-wise
  • Pick up Top Queries and Workflows for further action

Review plans with Humans in loop​

• Review queries and workflows suggestions
  • Review Queries generated will have deterministic implementations with runtime validations and policy checks suitable for your domain.

Implement plans with Confidence​

• Implement queries and workflows suggestions
  • Use GenAI help to customize, extend and complete use cases.
• Share the Queries and Workflows across users
• Easily implement any required AI integrations to existing or legacy systems.

Conclusion​

End Result → AI that will work consistently