Rigorous Evaluation Harnesses and Safety Guardrails for Production AI
We help enterprises deploy AI with confidence by creating automated evaluation test suites, red-teaming model prompts, detecting hallucinations, and enforcing compliance guardrails.
Primary Architecture
AI Evaluation & Safety
Modular · Resilient · Cloud Native
Challenges This Solves
- Fear of reputational damage from toxic, biased, or hallucinatory AI responses
- Inability to objectively measure whether a prompt or model update made the system better or worse
- Prompt injection attacks bypassing basic application instructions
- Lack of compliance tracking for emerging AI governance regulations
What Code Rockers Offers
- Automated LLM-as-a-judge evaluation benchmarks for accuracy and groundedness
- Adversarial red-teaming to uncover prompt injection and jailbreak vulnerabilities
- Runtime guardrails (NeMo Guardrails, Llama Guard) filtering unsafe inputs and outputs
- PII/PHI detection and dynamic anonymization before data reaches model providers
- Continuous production monitoring for semantic drift and regression tracking
Key Deliverables
Clear, concrete artifacts handed over to your team upon milestone completion.
Suitable Use Cases
Scenarios where this technical engagement yields immediate commercial value.
Engineering & Implementation Process
Golden Dataset Creation
Curate representative prompt-response pairs including edge cases and adversarial inputs.
Automated Benchmarking
Establish baseline scores across correctness, relevancy, and safety.
Guardrail Implementation
Install input sanitizers, output filters, and model safety wrappers.
CI/CD Integration
Block prompt changes or model swaps that degrade baseline benchmark scores.
Related Services
Frequently Asked About AI Evaluation & Safety
Ready to Begin Your AI Evaluation & Safety Project?
Let's review your objectives and map out a concrete architecture. Schedule a free 30-minute consultation with our engineering team today.