AI-Native Systems

RAG and agent architecture, LLM red teaming, evals, guardrails and model governance.

AI-Native Systems

RAG and agent architecture, LLM red teaming, evals, guardrails and model governance.

AI-Native Systems

RAG and agent architecture, LLM red teaming, evals, guardrails and model governance.

Overview

An agent with tools is a new trust boundary. The model reads untrusted text and then decides to act, which means prompt injection is not a content problem but an authorization problem.

We architect these systems and we red-team them, including the ones our clients built themselves.

What is covered

  • RAG and agent architecture

  • LLM red teaming

  • Prompt-injection testing against real tool access

  • Evals

  • Guardrails

  • Model governance

How it runs

Five stages: Scope, Recon, Exploit, Report, Retest. Anything critical is reported within the hour it is confirmed. The retest is included.

What you get

  • Injection paths demonstrated against the real tool surface

  • Guardrails tested, not assumed

  • Evals you can keep running after we leave

  • A retest once the fixes land