Policy

Secure Use of LLMs

GenDB: Using Enterprise IT Telemetry with GenAI Sensibly and Securely

Last Updated: April 16, 2024

Overview

What is GenDB?

GenDB is NeuBird AI's GenOps-based virtual database that enables secure and sensible read-only access to IT telemetry to solve ITOps problems. It is the foundation of how NeuBird AI uses large language models responsibly, without exposing your sensitive production data or internal intellectual property.

GenDB operates iteratively: it strips sensitive identifiers such as IP addresses and PII before sharing operational context with LLMs for guidance, then independently executes telemetry queries within your secure internal systems. This architecture ensures sensitive data never leaves your VPC while still leveraging AI capabilities for problem-solving.

Two Golden Rules

How NeuBird AI uses LLMs responsibly

Rule 01

Don't send your data to an LLM

The LLM never sees your specific telemetry with sensitive data such as IP addresses and personally identifiable information. Sensitive identifiers are stripped before any context is shared. The platform queries LLMs for advisory guidance while executing all real database queries locally within your VPC.

  • Sensitive identifiers (IPs, PII) stripped before LLM context is shared
  • Actual queries executed locally within your VPC
  • Zero exposure of sensitive operational data to third parties
Rule 02

Don't get IP from an LLM

NeuBird AI does not use LLMs to generate proprietary code for product development and does not extract intellectual property from LLM interactions. We use AI to solve operational problems, not to build competitive advantage on the back of your data or third-party model knowledge.

  • No proprietary code generated by LLMs for NeuBird AI products
  • No IP extraction from LLM interactions
  • AI used for operational guidance, not product development

How It Works

The GenDB workflow

1

Anonymized scenario sent to LLM

GenDB constructs a hypothetical, anonymized representation of the ITOps problem and sends it to the chosen LLM for advisory guidance.

2

LLM returns advisory guidance

The LLM responds with suggested query strategies and approaches based on the anonymized scenario: no actual data is involved.

3

Queries executed inside your VPC

NeuBird AI executes the actual telemetry queries locally within your VPC, against your real data, using the guidance from step 2.

4

Problem resolved, data stays internal

The ITOps problem is resolved using AI intelligence combined with your real data, none of which ever left your secure environment.

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