Guardrails

AI Guardrails You Control: Secrets, Personal Data & Safety Scans on the Request Path

Cloptima keeps credentials out of every prompt, applies the personal-data rules you define, and routes content to Azure AI Content Safety, AWS Bedrock Guardrails, Google Model Armor, or your own webhook — with your choice of what happens when a scan cannot run, and versioned, audited profiles.

app.cloptima.ai/llm/policies
Guardrail cost governance
Last 30 days · production policies
Illustrative
Requests scanned
402.5K
Blocked before egress
12.1K
Recent guardrail events
Secret detected in prompt
app=code-review-agent · blocked
Blocked
Email address redacted
profile v3 · custom rule email_address
Redacted
Provider scan timed out
request continued on local rules
Not checked
The problem

Guardrails shouldn't be a one-size-fits-all switch

Most gateway guardrails are all-or-nothing and tuned by the vendor. Teams get surprise blocks on legitimate traffic, or miss the coverage their region requires, and heavy safety scans add cost to every call.

  • Vendor-tuned defaults block traffic you never asked to block
  • Personal-data formats differ by country, so one global detector rarely fits
  • Heavy semantic scans add cost and latency on every call
  • Guardrail changes need an owner, a version history, and an audit trail
How it works

Your profiles, merged by strictest rule

A guardrail profile protects the data in every request before the model sees it. Switch on Cloptima templates, add your own rules, and redact or block each match. Content safety adds checks for prompt injection and harmful content.

  • Cloptima templates for credentials, regional personal data, finance, and health
  • Your own rules for business terms, each set to redact or block
  • Redacted values return in the response, so your app keeps working
  • An org baseline that teams can tighten but never loosen
Day one

Watch first, then redact, then block

Attach a profile to a policy in Monitor only and see what it would redact or block, with no change to your traffic. Then enforce the policy, move the cases that must never reach a model to block, and make the profile your organization baseline.

Architecture

Cost and outages stay in your hands

Local rules run inside the gateway with no extra network call, so a request they block never pays for a scan. If a provider scan cannot run, each profile chooses: keep traffic flowing on your own rules, or block. Unchecked requests show as Not checked, and every profile change is versioned and audited.

Developer quickstart

Keep your SDK, change the base URL

The gateway speaks the OpenAI and Anthropic protocols. Point your existing client at it and add attribution headers.

bash
curl https://api.cloptima.ai/v1/ai/chat/completions \
  -H "Authorization: Bearer $CLOPTIMA_PAT" \
  -H "X-Cloptima-Team: security" \
  -H "X-Cloptima-App: customer-support-agent" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6",
    "messages": [{"role": "user", "content": "Debug this config: api_key = abc123def456ghi789"}]
  }'

# The bound guardrail profile checks the prompt before it reaches the provider:
# HTTP/1.1 403 Forbidden
# {"error": "Your AI request was blocked because it matched a configured safety rule.", "reason": "gateway_guardrail_blocked", "violations": ["secret_assignment"]}
Get started

Launch path

Create a profile from a template, make it your organization baseline, optionally add a provider scan and choose what happens if it cannot run, attach profiles to policies, and watch findings in the audit log.

FAQ

Questions teams ask

Put your first governed call through in five minutes

Point your SDK at the gateway, bind a policy, and watch the first call land on the ledger.

No credit card required
5-minute setup
Free plan