AI Development
AI features engineered with data governance and prompt-layer security.
Development of AI-enabled features and platforms with attention to data governance, prompt injection resistance, output handling and auditability.
- Typical timeline
- Typically 6–16 weeks depending on scope
- Business benefit
- Adopt AI capability without creating an unmanaged data and trust boundary.
- Industries
- Banking & Financial ServicesHealthcareE-CommerceIT & Cloud ServicesGovernmentManufacturing
Overview
What AI Development covers
AI features introduce new trust boundaries: untrusted content reaching a model, model output reaching privileged systems, and sensitive data reaching third-party providers.
We design those boundaries explicitly, with authorisation enforced outside the model and every action auditable.
The problem we solve
AI features are frequently shipped with model output trusted implicitly and sensitive data flowing to providers without governance.
Scope & outcomes
What we test and what you receive
Scope coverage
- Use case definition and data governance
- Retrieval and context architecture
- Prompt injection and content isolation
- Output validation and safe tool invocation
- Authorisation enforcement outside the model
- Sensitive data minimisation and redaction
- Evaluation, guardrails and monitoring
- Cost, latency and reliability engineering
Key benefits
- Controlled exposure of sensitive data
- Resistance to prompt injection and misuse
- Auditable AI-driven actions
- Predictable cost and performance
Deliverables
- Solution architecture and threat model documentation
- Production-ready source code with review history
- Automated test and security check coverage
- Deployment, environment and secrets configuration guide
- Handover walkthrough and technical documentation
- Post-release support window
Methodology
Our assessment process
- 01
Use case and feasibility assessment
- 02
Data inventory and governance review
- 03
Architecture and threat model for the AI layer
- 04
Prototype and evaluation harness
- 05
Iterative development with guardrails
- 06
Adversarial testing of the prompt and tool layer
- 07
Monitoring and audit trail implementation
- 08
Deployment and rollout
- 09
Ongoing evaluation and tuning
Tooling
Tools and techniques
Tooling supports expert manual testing — it never replaces it.
FAQ
AI Development questions
Yes. We design data flows around your governance requirements, including redaction, regional processing and self-hosted model options.
Yes. Prompt injection, tool abuse and authorisation bypass through the model layer are part of our testing scope.
Related
Other services in this category
Ready to scope AI Development?
Talk to our offensive security team about scoping an assessment around your actual risk, stack and timelines.
Prefer email? business@securityloyals.com