One control plane to govern every AI model, agent and LLM, from code to deployment to runtime, with compliance, risk, approvals and live LLM guardrails built for the MENA region.
Gradient Governance: AI Governance & Sovereignty
Interactive demo running entirely in the browser on a real captured snapshot of a live DataRobot-connected workspace (governed models, policies, approvals, LLM usage, incidents and reports). Reads are faithful; write and AI actions are simulated in-session. Production runs an Express + Prisma backend connected to DataRobot, Databricks and your own LLM endpoints.
Problem
Enterprises are shipping ML models, GenAI apps and agents faster than any team can govern them. Model inventories live in spreadsheets, compliance to the EU AI Act and SDAIA is proven after the fact, approvals happen over email, and LLM usage runs ungoverned with no view of cost, PII exposure or jailbreaks, across DataRobot, Databricks and in-house stacks.
Approach
Gradient Governance is a provider-neutral control plane that syncs models, deployments and agents from connected platforms and governs their full lifecycle: automated risk tiering and compliance qualification (EU AI Act, SDAIA, ethical-AI), multi-stage approval workflows with security gates, an LLM gateway that wraps your endpoints to meter token cost and enforce guardrails (PII, jailbreak, MCP and tool guards), prompt registry with versioned approvals, end-to-end lineage from code to runtime, incident management, and board-ready reporting, all under role, organisation and business-unit RBAC.
Outcomes
