Pragmatic plans for using internal AI safely
We bypass the generic marketing hype around AI to construct secure, predictable, and fully audited planning guidelines for language models.
Identifying real-world use cases
Integrating large language models (LLMs) requires structured preparation. Feeding poorly formatted, unorganized text documents into a model leads to incorrect outputs, confusion, and potential privacy issues.
We work with UK service teams to define the specific problem, map database layouts, and establish clear guidelines before any code is written.
Security Notice: Language model outputs are probabilistic and require ongoing human validation. Our planning guides do not replace official compliance, regulatory, or legal approvals.
Our AI Readiness Assessment Framework:
- Target Selection: Narrowing down complex processes to simpler, high-value assistant tasks.
- Document Mapping: Reviewing text formats to ensure systems find accurate context.
- Information Control: Restricting access permissions to keep sensitive data private.
- Review Processes: Designing human-in-the-loop steps to verify all generated answers.
Starting Inputs Needed:
To run an assessment, we start by reviewing your active knowledge bases, cataloging current text files, and mapping team roles to ensure data is handled securely.