AI Governance

AI governance with complete audit trail, granular agent control, and cost attributed per interaction. Ready for EU AI Act, LGPD, and board.

Your company is running AI you don't control

Right now, agents are making decisions, sending data, and acting on behalf of your company. Regulators are already asking who's accountable. Jumpad puts structured governance where today there's only speed.

Three risks that grow as AI adoption advances without governance

001
Liability without an owner

When an AI response supports a wrong decision, sustains a document, or exposes sensitive information, who's accountable? Without a record of the interaction, the answer is "nobody knows." That doesn't pass auditors, regulators, investors, or boards. Organizations with high shadow AI use recorded an average breach cost US$ 670K higher than those with low shadow AI use. (IBM Cost of a Data Breach Report, 2025)
002
Cost without attribution

AI tools acquired without centralized visibility. Consumption distributed across teams, accounts, and models, without attribution by agent or interaction. The company pays for capacity it can't attribute. Jumpad delivers cost attribution per interaction, per agent, and per area.
003
Model lock-in

If the knowledge base was indexed with one provider's model, switching models means rebuilding everything. Dependency installs itself before it's noticed. Jumpad operates as an LLM and cloud-independent layer: knowledge stays in the company, not in the model.

Control, sovereignty, and traceability. The three pillars of AI Governance

Control
Visibility of every prompt, agent, and model in operation. Audit trail of every interaction. Cost control per agent, per area, and per purpose. Every behavior within the defined perimeter. Every expense attributed.
- Access policies by profile, team, and data sensitivity
- Guardrails that block out-of-scope behaviors before they happen
Sovereignty
Jumpad connects your LLMs via API, not through consumer interfaces, where data usage policies differ. You control which models are active, which providers have access, and which policies apply to each interaction.
- Defined jurisdiction for LGPD and EU AI Act compliance
- Centralized control of providers and models in the Model Hub
Traceability
Every interaction is recorded with the prompt sent, the model used, and the responsible agent, forming traceable and auditable information. Ready for regulators, investors, and board.
- Automated compliance report for audit
- Evidence of who asked what, to which model, and with which data

An independent layer. Any LLM. Any system.

Connects

Jumpad connects your LLMs (OpenAI, Anthropic, Google, Azure) and corporate systems (CRM, ERP, internal apps) in a single governance layer.
Intermediates

Every interaction passes through Jumpad's layer. Prompts, responses, cost, and responsible agent are recorded automatically. Guardrails block out-of-scope behaviors before they happen.
Delivers visibility

Centralized dashboard with cost per agent, per area, and per model. Complete audit trail. Compliance report ready for regulators and board.

Governed AI generates advantage. AI without governance generates exposure.

Before

Operation without governance

Agents operate without tracking

Distributed costs without attribution

Liability without an owner

Knowledge retained by providers

Growing regulatory exposure

Shadow AI without centralized visibility

After

Operation with AI Governance

Every interaction recorded and auditable

Cost by agent, department, and model

Traceable accountability for every interaction

Knowledge under company control

Audit trail ready for the EU AI Act and LGPD

AI usage visible and governed

AI adoption arrived before governance. Risk lives in that gap

The EU AI Act is in force. Penalties already apply: up to €35 million or 7% of global annual revenue for prohibited practices. In Brazil, Art. 20 of the LGPD guarantees the right to request review of decisions made solely based on automated processing — and Jumpad delivers the record required when someone asks how the result was produced.

88% of organizations report regular AI use in at least one business function. Nearly two-thirds haven't moved beyond pilots. Adoption came first. Governance hasn't caught up yet. (McKinsey, The State of AI, 2025)

Every interaction without a record has no owner. Every month without an audit trail is exposure that can't be reconstructed retroactively. Companies that structure AI Governance now arrive at growth with a compliance history and a solid foundation for audit. Those who wait rebuild from zero when the regulator asks.