AI Evals, Red-Teaming and Guardrails
Most AI failures are not crashes. They are confident wrong answers nobody measured. We build the measuring: test suites from your real cases, attacks tried on purpose, and checks that run on every change and every day in production.
In short. AI Evals, Red-Teaming and Guardrails is one of Matrida Infotech's AI services. Know whether your AI works before you ship it, and keep knowing after: evaluation suites, red-teaming, guardrails and live monitoring. Typical stack: Langfuse · Promptfoo · Ragas · LangSmith · policy and PII filters · OpenTelemetry.
Sound familiar?
- Nobody can say if the new prompt or model is better or worse
- A customer found a failure before you did
- Security asks how you test for prompt injection and data leaks
- Quality slipped after a model update and you noticed weeks later
Capabilities
- Evaluation suites
- Red-teaming
- Guardrails and policy checks
- Prompt-injection testing
- Drift and quality monitoring
- Human review workflows
What we build
- Evaluation sets built from your real cases, scored automatically and by reviewers where judgement is needed
- Red-team exercises: prompt injection, jailbreaks, data extraction and unsafe-action attempts
- Guardrails for personal data, off-topic requests, policy limits and risky actions
- Live monitoring for quality, cost, latency and drift, with alerts
- A release gate: no prompt or model change ships if the scores drop
What you get
- Evaluation suite and regression dataset
- Red-team report with fixes
- Guardrail configuration and test results
- Monitoring dashboard and alert rules
Tools and frameworks
- Langfuse
- Promptfoo
- Ragas
- LangSmith
- Guardrails frameworks
- OpenTelemetry
Where it fits: Financial Services, Healthcare.
Questions
How do you evaluate an AI that gives open-ended answers?
With a mix of checks: exact checks where an answer can be verified, rubric scoring by a model that is itself checked against human ratings, and human review on a sample. We report how far each method can be trusted.
What does red-teaming actually involve?
We attack the system the way a hostile user or a poisoned document would: hidden instructions in files, attempts to extract other users' data, requests to take actions it should refuse. Every finding comes with a fix and a test that keeps it fixed.
Can you evaluate a system someone else built?
Yes. An independent evaluation is often the fastest way to find out whether a vendor or an internal pilot is ready.
Do guardrails slow the system down?
Some add a small delay. We run cheap checks first and expensive ones only when needed, and we measure the added latency so you can decide.
Related services
AI Agent Development
We build AI agents that complete multi-step work inside your systems, with guardrails, human approval and full audit logs.
Learn more →RAG & Enterprise Knowledge Assistants
Private assistants that answer from your documents with citations, permission-aware retrieval and measured accuracy.
Learn more →Generative AI Application Development
Customer-facing and internal LLM products, from document drafting to AI copilots inside your SaaS.
Learn more →Planning AI Evals and Guardrails? Tell us the workflow.
Say what is going wrong today. We reply with how ai evals, red-teaming and guardrails would handle it, a rough scope and the first thing to build.
- You would get: evaluation suite and regression dataset
- You would get: red-team report with fixes
- You would get: guardrail configuration and test results