Infobelt AQL-Copilot™

On-Prem | Cloud | Hybrid

Infobelt AQL-Copilot™

GenAI powered Archive Query Language

Retrieve and export structured data from archives efficiently using intuitive natural language prompts.
Infobelt AQL Copilot AI-powered archive query language for enterprise data retrieval

AQL-Copilot™ Transforms Data Retrieval with Natural Language Queries

AQL-Copilot™, short for Archive Query Language & Libraries, has been designed and built with one purpose – leverage GenAI to interpret natural language, understand the data model including entity relationships, write/execute complex queries and present the results to the end user in a reporting format of choice; ad hoc and near real time. Ex: This is similar to prompting with ChatGPT.
User-Friendly Interface
User-Friendly Interface

Intuitive Chat GPT-like interface suitable for business, legal & corporate users. Maintain history of prompts and the respective responses.

Encrypted Data Handling
Encrypted Data Handling

AQL-Copilot™ allows you to manage your data in a secure way using encryption and features such as password protection and sensitive data masking.

Exporting data to various<br> formats
Exporting data to various
formats

After querying the archive, the resulting data can be exported to multiple formats such as CSV, JSON, SQL.

Access data from a single archive or collection of archives
Access data from a single archive or collection of archives

AQL-Copilot™ allows you to query a single archive or a collection of archives (collated from multiple databases)

Cost Savings
Cost Savings

The reduction in time spent on manual processes translates into cost savings, allowing resources to be allocated more effectively across the organization.

Integration Capabilities
Integration Capabilities

The system integrates with existing database archives ensuring that users can leverage their current infrastructure. AQL-Copilot™ Benefits for Businesses

Increased Efficiency
Increased Efficiency

By automating and enabling repeatability of query generation and reporting, AQL-Copilot™ significantly reduces the time and effort required for data analysis tasks.

Enhanced Productivity
Enhanced Productivity

Generate complex reports from archived data using simple English language prompts and queries. Saves time and effort.

Dynamic Query Generation
Dynamic Query Generation

AQL-Copilot™, based on user requests, dynamically analyzes the data model, learns which tables are needed to answer the query, generates and executes SQL queries allowing for quick and efficient data retrieval.

Improved Data Accessibility
Improved Data Accessibility

AQL-Copilot™ enables authorized team members to access and retrieve critical information for their daily operations and regulatory requirements without having to learn the technology intricacies All the while conforming to fine grained entitlements and ensuring data security.

Empowering business users with AI tools for archived data retrieval

AQL-Copilot™ represents a significant advancement in how organizations interact with their archived data. By combining ease of use with powerful features, it empowers businesses to harness their historical data effectively, driving better outcomes and fostering a culture of data-driven decision-making.
Infobelt Omni Archive Manager AI-powered enterprise data archiving platform

Infobelt's AI Copilot Transforms Audit

Regulatory Response at the Speed of Business: For one of the world's largest banks, Infobelt revolutionized the audit process. Our advanced eDiscovery and AI-powered AQL Copilot™ allow legal teams to perform targeted searches across 30+ trillion records, reducing the time and effort required for regulatory reporting and litigation response from weeks to seconds.

Resources

Data archiving blogs and whitepapers

Frequently asked questions

Frequently asked questions focused on architecture, interoperability, scalability, and enterprise readiness.

What is AQL Copilot and how does it simplify data retrieval?

AQL Copilot (Archive Query Language) is an AI-based tool that allows users to retrieve and export structured data from archives using intuitive natural language prompts. Instead of writing complex code, business, legal, and corporate users can use English language prompts to interact with their data through a user-friendly interface.
Does AQL Copilot require technical knowledge to generate SQL queries?
No. AQL Copilot automatically generates SQL queries based on user inputs. This empowers non-technical business users to harness historical data for decision-making without needing to understand the underlying database schema.
What is the benefit of “Semantic Search” in AQL Copilot?
Semantic search interprets the meaning and intent behind a query rather than just matching keywords. This enhances data retrieval by providing contextual accuracy—for example, matching a query for “staff manual” to “company policies”—and allows for more precise and efficient discovery within large archived datasets.
In what formats can I export data using AQL Copilot?

AQL Copilot allows you to export your retrieved data to multiple standard formats, including CSV, JSON, and SQL. It also maintains a history of all prompts and their respective responses for future reference.