Adversarial users don't show up during happy-path testing. They show up the week after you launch, with time on their hands.
AI Guardrails
Your users are creative. More creative than your happy-path tests.
I help teams add moderation, prompt defenses, policy enforcement, evals, and human-review escape hatches that fit the product they actually have today. The goal is not security theater. It's practical guardrails that let agentic features keep moving — with evidence that they're not going sideways.
Best fit
AI Guardrails Consulting
- Guardrail architecture and threat model for your current product
- Recommended moderation and eval stack with cost and latency tradeoffs
- Policy matrix for unsafe content, prompt attacks, PII, and tool misuse
- Implementation roadmap your team can ship in phases
Fast
Retrofit into existing AI flows
Lower
Moderation cost through layered checks
Clear
Policies engineers can implement
Why teams call
The pattern I keep seeing.
Teams often overspend on blanket moderation calls when a layered policy engine would catch most issues for far less.
A safe demo is not the same thing as a production-safe agentic workflow with logging, evals, escalation, and recovery paths.
What changes
What actually gets better.
Map every risky AI interaction across input, retrieval, tools, output, and logging.
Design layered moderation so cheap deterministic checks absorb routine policy issues before expensive model reviews fire.
Add trust controls like rate limiting, review queues, redaction, quarantine, eval gates, and escalation paths.
Document guardrail coverage so product, engineering, and leadership all understand residual risk.
How I work
No mystery, no handoff decks.
01
Inspect the real traffic
We start with the prompts, retrieval payloads, tool calls, and failure modes your app already sees instead of designing for imaginary users.
02
Layer the controls
I combine cheap static rules, contextual classifiers, and targeted model-based moderation only where they add real value.
03
Build for operations
The final design includes observability, human review, safe fallbacks, and incident response so the controls stay useful after launch.
Next step
Ready to stop circling it?
Bring whatever your team keeps putting off — the scary migration, the expensive AI bill, the app that misbehaves in production. We'll figure out what's actually blocking it.
