Prompt inspection
Tuned, quantized local AI models identify sensitive content. The current PoC validates text inspection and basic hard blocking.
VALIDATED IN LOCAL POCA local-first prompt security gateway in development. Designed to inspect AI requests, block sensitive content, and give security leaders a clearer view of enterprise AI use.
Employees use generative AI to move faster. Customer records, internal reports, and proprietary code can travel with them. RiskorAI focuses on inspecting this conversational boundary.
Tuned, quantized local AI models identify sensitive content. The current PoC validates text inspection and basic hard blocking.
VALIDATED IN LOCAL POCPlanned placeholder substitution will mask sensitive data, with hard blocking when redaction would damage the prompt’s context.
PLANNED / PHASE 2Base administrative logging is established. Centralized policies, reporting, and a tamper-evident audit vault form the next development scope.
BASE LOGGING / POCSwitch between two predefined examples to understand the hard-block concept. This is an interactive illustration, not a running AI security engine.
This example contains a personal identifier. In the PoC hard-block flow, a flagged request is rejected before forwarding.
Designed for CISOs, risk leaders, and data protection teams in organizations with managed or corporate-owned devices—especially banking, financial services, telecom, and B2B SaaS.
Local Windows prototype, lightweight model execution, basic hard blocking, and foundational administrative logging.
Migrate to a dedicated TLS forward-proxy appliance and validate interception, latency, and operational behavior in managed environments.
Add contextual sanitization, semantic anomaly detection, tamper-evident logs, and centralized security policy management.
No. The current implementation is a local Windows proof of concept. A network-edge appliance with SSL/TLS forward proxy is a planned migration. Deployment will require approved enterprise device and network configuration.
The PoC uses local, optimized AI models for inspection. The proposed appliance architecture also keeps security parsing local. Permitted prompts may still be sent to the organization’s chosen external AI service.
No. The brief states a target of up to 95% prevention of accidental leaks. It does not supply a measured benchmark or test methodology, so this page makes no verified detection or prevention claim.
The planned model combines an enterprise appliance license with a subscription based on prompt filtering volume or throughput. Pricing, service levels, integrations, and production availability are not finalized.
No. RiskorAI aims to support data governance and evidence collection. Compliance depends on an organization’s full technical, legal, and operational controls, and requires independent assessment.
Exploring AI governance for your organization? Talk to our founding team about your environment and potential pilot requirements.