AI Security & Guardrails

Overview

What we deliver

We build security layers and guardrails that protect your AI systems from prompt injection, data leaks, and unsafe outputs.

AI systems introduce new attack surfaces: prompt injection, jailbreaks, data exfiltration through tool calls, and unsafe model outputs. We build defense layers that protect your applications without breaking user experience. Our work includes input sanitization, prompt firewalls, output filtering, PII redaction, tool-use policies, rate limiting, and audit logging. We integrate libraries like Guardrails AI, NeMo Guardrails, Llama Guard, and custom classifiers tuned to your risk model. We also run red-team exercises against your AI features to find weaknesses before attackers do, then patch them with layered controls. For regulated industries, we map controls to frameworks like NIST AI RMF, ISO 42001, and EU AI Act requirements. Every engagement produces a threat model, control inventory, test suite, and monitoring setup so your security team has visibility into AI risk. We aim for practical safety, not theater.

Fit Check

Built for teams like yours

Who it's for

AI product teams
Compliance and risk leaders
Enterprise security teams
Fintech and healthtech
Customer-facing AI apps

Pain points we solve

Prompt injection vulnerabilities
Sensitive data in prompts and outputs
Unsafe or off-brand responses
No audit trail for AI decisions
Unclear compliance posture

What's included

Capabilities

Everything we cover in this engagement.

AI threat modeling
Prompt injection defenses
Input and output filtering
PII detection and redaction
Tool-use policy enforcement
Red-team testing
Audit logging and observability
Compliance mapping (NIST, ISO, EU AI Act)

How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Threat model

We map attack paths and data flows in your AI system.

02

Controls design

We pick guardrails and filters matched to your risks.

03

Implementation

We integrate guardrail libraries and custom classifiers.

04

Red team

We attack the system and refine controls until it holds.

05

Monitoring

We set up logging, alerts, and ongoing review.

What you get

Deliverables & outcomes

What you get

Threat model document
Guardrail integration code
PII redaction pipeline
Red-team report
Audit logging setup
Compliance control mapping

Outcomes you can expect

Lower prompt injection risk
No sensitive data leakage
Consistent on-policy outputs
Audit-ready AI logs
Faster compliance reviews

Timeline

3 to 6 weeks

Engagement

Monthly retainer, Project, Sprint

Tools we use

Guardrails AI, NeMo Guardrails, Llama Guard, Presidio, OpenAI Moderation

KPIs we track

Injection block rate, false positive rate, PII leak incidents, policy violations, audit coverage

Client stories

What clients say

"

Our LCP was 4.8 seconds and Google was punishing us for it. They audited the build, dumped two plugins we did not need, moved hero images to a real CDN, and rewrote the critical CSS. LCP came down to 1.6 seconds within three weeks. Bounce rate on the pricing page dropped by a quarter without us touching the copy.

Sarah K.

"

We were drowning in tier-one tickets about password resets and appointment changes. They built a deflection layer on top of our help desk and kept their agents in the loop for anything sensitive. Volume to humans dropped 58 percent in two months and our patient NPS held steady. The hybrid handoff is the part most vendors get wrong. They did not.

P.M.

Proof