Your engineers are shipping with AI. Your CISO is asking questions you can't answer.
AI adoption is outpacing governance. Here's what that looks like at scale.
15 teams using different models, different API keys, zero centralized logging. Every team ships AI features independently — and governance catches up after the fact.
Your board asks: "What customer data is going to which AI provider? Show us the audit trail." Without a control layer, you can't. Every procurement review becomes a scramble.
Every new AI tool adds another path for data to leave your network. No policy engine. No enforcement. No way to prove what did or didn't go to a third-party model.
One lightweight Go proxy. Deploy once. Every AI call flows through it.
No code changes. No SDK. One environment variable routes your AI traffic.
One Go binary. Deploy on localhost:9090. Every AI call flows through it. No orchestration, no sidecars, no infrastructure sprawl.
Enforce rules before data reaches any model provider. Block, flag, or log by model, team, data classification. Policies deploy as JSON — seconds, not sprints.
Anthropic, OpenAI, DeepSeek, any OpenAI-compatible endpoint. One proxy. One policy language. One audit trail. Your model choices shouldn't dictate your governance.
Every call logged — which model, which team, what data classification, what policy was applied. JSONL output, consistent schema, SIEM-ready.
Single pane of glass.
One dashboard shows which models are used, by which teams, with what data classification. Audit trails that survive any procurement review. Policy engine: block, flag, or log by model, team, data sensitivity. Your CISO gets a dashboard. Your engineers keep their tools.
Procurement-ready.
Shield maps to the standards your compliance team lives by. Here's how each control maps.
Shield's policy engine maps directly to SOC 2 control activities. Every model call passes through enforceable rules with structured audit evidence — satisfying the CC5.1-CC5.3 criteria for control design, implementation, and monitoring.
Shield produces structured JSONL audit logs with consistent schema covering event type, timestamp, model, team, and policy action. Maps directly to A.12.4.1-12.4.3 logging, monitoring, and clock synchronisation controls.
Shield's audit trail provides a complete, queryable record of every AI processing activity — which data classifications were sent to which processors, under which policies. Satisfies Article 30 processing record requirements out of the box.
Write JSON policies targeting specific models, teams, or data classifications. Deploy in seconds. No vendor lock-in — your governance rules are plain JSON under your version control.
Flat price. Deploys in one week.
FLAT · ONE WEEK
Full governance suite. Policy engine, audit logs, dashboard. Everything you need to answer your CISO's questions.
FLAT · ONE WEEK
Multi-region deployments, custom SIEM integration (Splunk, Datadog, Elastic), dedicated support, federated dashboard across regions.
Published pricing · No per-seat or per-token meter · Two PO line items
Let's Build.
Submit your technical details and we will formulate a production scope, architectural dependencies, and exact model selection profiles.