Know before it goes
Your team is already using AI. The question is whether you know what they are sending — and to whom.
The Enterprise AI Privacy Gateway sits between your users and every LLM provider. Before any prompt reaches OpenAI, Anthropic, Grok, Gemini, or a self-hosted model, it passes through a privacy inspection layer that detects sensitive content, applies redaction policies, and logs everything internally.
What you get on day one
- Full prompt audit log, searchable and exportable.
- PII scan results for every outbound request.
- Executive dashboard showing data egress risk score, cost breakdown by provider, and automated insights.
- Multi-provider routing across five LLM providers, each called at its enterprise endpoint, with zero data retention where the provider offers it.
- Automated prompt recommendations that surface cost and risk reduction opportunities.
Why this is the AI story enterprises actually need
Most AI governance conversations start at the policy layer. This starts at the data layer — every byte before it moves.
It answers the question no compliance officer can ignore: what business data has left this building through an AI prompt, and who saw it?
White-label for your clients
Deploy the full platform under your own brand. Your clients get their own private gateway, isolated vector store, and executive dashboard. You retain the relationship. We run the infrastructure.
Why dev3lop
A privacy gateway is a data engineering problem before it is an AI problem. Every prompt is a record that has to be inspected, logged, attributed to a user and a provider, and rolled up into reporting someone will actually read. DEV3LOPCOM, LLC is an Austin, Texas data engineering consultancy, and that is the work we have done for years — including pipelines for Nielsen that handled trillions of records. We are 100% onshore, and our founder is a former Tableau Software Professional Services consultant, so the egress dashboard is built by people who have shipped executive reporting before.
The gateway is one layer of a larger agent program. When you want models built into your own products, with routing, cost controls, and fallbacks behind them, that work runs through our LLM integration practice. If you are still deciding which workflows to automate, start with our AI agent consulting. If you are packaging agents for your own customers, pair the gateway with our workspace agent marketplace consulting — tenant isolation, usage metering, and audit trails are the same engineering problem on both sides.
See what is leaving today
Bring us the AI tools your team already uses and the data you are most worried about. We will show you where the gateway sits in front of those providers and which policies to turn on first. Contact us to scope a deployment.