CISO & security teams
Pain: Agents are reaching sensitive data with broad standing access and no audit trail.
Fit: Zero-standing, just-in-time grants and real-time policy enforcement on cloud data platforms.
Practice · AI Governance & Trust
Deploy agents faster, with the right data
We help enterprises stand up a Unified Trust Layer for AI agents — purpose-based access control, just-in-time grants, agent discovery and audit-ready evidence — so you can ship agentic AI without losing control on Databricks, Snowflake and multi-cloud estates.
Yerbabuena Digital
Yerbabuena Digital brings hands-on agentic AI governance experience to your AI program. We design purpose-based access policy and author audit-ready evidence — your platforms enforce it; regulators read our artifacts. That includes just-in-time grants, LLM guardrails, gateway integrations, agent discovery and Trustscore evaluation — aligned to EU AI Act and GDPR programs for finance, healthcare and government.
Who this practice is for
Organizations moving from AI pilots to production who need governance that auditors accept and engineers can live with.
Data & AI leaders
Pain: AI governance is slides and spreadsheets; nothing enforces policy at the data plane.
Fit: Purpose-based policy design and evidence your platforms can enforce on Databricks, Snowflake and multi-cloud estates.
Risk, compliance & legal
Pain: EU AI Act and GDPR obligations with no evidence trail for agents and models.
Fit: Agent discovery, Trustscore evaluation and audit-ready evidence for regulated industries.
Governance at the data plane, not on paper
Most AI governance programs stop at policy documents. We design purpose-based access control (PBAC) and author the evidence — zero standing access, just-in-time grants that expire — while your access platforms enforce the rules at the data plane.
We build a Unified Trust Layer across your AI stack: gateways (Portkey, LiteLLM, Kong), MCP-aware policy, and integration with Databricks, Snowflake and multi-cloud estates — we implement around your tooling; we do not sell a replacement platform.
Agent discovery and observability close the loop: we inventory every agent, what it can reach, and how it performs — with Trustscore-style evaluation and tracing across heterogeneous frameworks.
The output is audit-ready evidence — who/what accessed what, for what purpose, when, and with what approval — mapped to EU AI Act and GDPR obligations. That is what boards, regulators and your CISO will ask for.
Every governed pilot ends with an Evidence Pack.
Not a slide deck — a working system plus the artifacts your security, legal, and compliance teams need to approve going further:
- Inventory of every agent, model, tool, and data scope in the pilot
- Access policy design: purpose-based control, just-in-time grants, zero standing access
- Audit-trail export: who/what accessed what, for what purpose, with what approval
- Evaluation baseline: accuracy, cost, and failure behavior measured against agreed criteria
- Risk memo mapped to the specific EU AI Act and GDPR obligations that apply to you
If the pilot doesn't produce its Evidence Pack, you don't pay the final milestone.
Return on investment
Where the numbers come from
Illustrative scenarios based on typical governance engagements — results vary by estate, tooling and scope. We scope every engagement together before you commit.
Bank — governed agent rollout
A financial services group wanted to let internal agents query customer data without giving standing access to sensitive tables.
- Standing access
- Zero — Just-in-time, purpose-bound grants
- Time to provision access
- Minutes — Was days of tickets
- Audit evidence
- 100% — Per-purpose, per-agent logs
PBAC + JIT lets agents move fast on sensitive data while auditors get exactly the evidence they need.
Healthcare — EU AI Act readiness
A provider deploying clinical-support agents needed evidence of purpose, data scope and human oversight for EU AI Act and GDPR.
- Agents discovered
- Full inventory — Tools, data, models mapped
- Policy coverage
- Enforced — At the data plane, not paper
- Audit prep effort
- −70% — Evidence exports on demand
Governance built at the data plane turns AI Act readiness from a project into a byproduct.
Capabilities
What we design and evidence
Policy design, platform integration and audit-ready artifacts — platforms enforce; regulators read what we author.
Unified Trust Layer
One control plane for agents, models and data access — designed by us, enforced by your platforms.
- PBAC policy design and purpose taxonomy
- Zero standing access with just-in-time grants
- Integration with your access and data platforms
- Audit-trail export mapped to EU AI Act and GDPR obligations
Agent discovery & observability
Know every agent and what it can do.
- Agent, tool and data-access inventory
- Trustscore evaluation and tracing
- Coverage across LangChain, CrewAI, Bedrock, Copilot, custom
- Drift, failure and anomaly detection
Gateway & MCP-aware policy
Enforce policy where agents call models and tools.
- Gateway integrations: Portkey, LiteLLM, Kong
- MCP-aware policy and A2A delegation security
- LLM guardrails and content policies
- Prompt and tool-call logging
Compliance evidence
Audit-ready proof for regulators and boards.
- EU AI Act readiness mapping and evidence
- GDPR data-purpose alignment and RoPA ties
- Per-purpose, per-agent access logs
- Evidence exports and review workflows
What you walk away with
Deliverables by engagement
We design purpose-based policy and author the proof — your platforms enforce it; regulators read our artifacts.
Discovery Workshop
- Current-state agent and model inventory
- Policy and access-control gap analysis
- EU AI Act / GDPR obligation map for your agents
- PBAC design outline and phased roadmap
Governed PoC / Pilot
- PBAC policy design with just-in-time grant workflow
- Gateway or platform integration proof
- Audit-trail export sample
- Evidence Pack (inventory, policy, evaluation baseline, risk memo)
Full Implementation
- Unified Trust Layer rollout across data estate
- Operational agent discovery and inventory
- Automated evidence pipeline for access events
- Board- and auditor-ready documentation pack
Governed Retainer
- Quarterly access reviews and policy updates
- Agent inventory refresh and drift reports
- Regulatory change impact assessments
- Pre-audit evidence preparation
Use cases
Where this lands hardest
Governed agent access to customer data
Challenge: Agents needed customer data for workflows; standing access was a regulator red flag.
Outcome: PBAC + JIT grants with per-purpose logs; agents move fast, auditors get evidence.
EU AI Act readiness for clinical agents
Challenge: Clinical-support agents with no purpose, scope or oversight evidence.
Outcome: Agent discovery, Trustscore and evidence exports mapped to EU AI Act and GDPR.
Audit-ready agentic e-Administration
Challenge: New AI functions with no enforceable policy or access trail.
Outcome: Unified Trust Layer with logging and exports aligned to e-Admin expectations.
Engagement
How a governance engagement runs
From discovery to enforced policy and audit-ready evidence — in clear phases.
Discover
We inventory agents, models, tools and data; map regulations and risk. You get a governance gap map and quick wins — not a generic framework.
Architect
We design the Unified Trust Layer: PBAC model, JIT grants, gateway and MCP policy, and the evidence pipeline — co-authored with security, data and legal.
Implement
We enforce policy at the data plane on Databricks, Snowflake and multi-cloud; wire gateways; stand up agent discovery and Trustscore evaluation.
Govern & evidence
We hand over runbooks and evidence exports — or run a governed retainer with monitoring, policy reviews and audit support.
Before & after
What changes with a trust layer
Before
- Policy on paper; broad standing access in practice
- No inventory of agents, tools or data reach
- Gateways and MCP with no enforceable policy
- AI Act and GDPR evidence assembled by hand each audit
After
- PBAC with zero standing access and JIT grants
- Agent discovery and Trustscore across every framework
- MCP-aware policy enforced at gateways and the data plane
- Audit-ready evidence exports on demand
Outcomes
What clients typically see
Ship agents faster
Clear guardrails and JIT access let teams move on real data without waiting for standing-access tickets.
Zero standing access
Purpose-bound, time-boxed grants replace permanent broad access — least privilege by construction.
Audit-ready by design
Per-purpose, per-agent evidence exports make EU AI Act and GDPR reviews a byproduct, not a fire drill.
One control plane
A Unified Trust Layer across models, gateways and data platforms — instead of scattered point controls.
Works with your platforms
Platforms enforce access; we design the policy and author the evidence regulators accept. We work around Databricks, Snowflake, Immuta-class access platforms, Holistic AI- and Saidot-class GRC tools, and Portkey, LiteLLM or Kong gateways — partner to your stack, not a replacement.
Frequently asked questions
Frequently asked questions
What is PBAC and how is it different from RBAC?
Purpose-based access control grants access for a specific purpose and time, not a permanent role. Agents get just-in-time, purpose-bound access that expires — far safer than standing role-based access for non-human callers.
Which data platforms do you enforce on?
Databricks, Snowflake and multi-cloud estates, with Apache Ranger-class lineage and enterprise access platforms. We meet your data where it lives rather than forcing a rip-and-replace.
Can you help with EU AI Act readiness?
Yes. We map obligations to your agents, models and data, then produce the evidence regulators expect — purpose, scope, human oversight and access trails.
Do you integrate with our LLM gateway?
We work with Portkey, LiteLLM, Kong and similar gateways, plus MCP-aware policy and A2A delegation security, so enforcement covers model and tool calls too.
What is agent discovery?
An inventory of every agent, the tools it can call and the data it can reach, plus tracing and Trustscore-style evaluation across frameworks — so nothing is shadow.
Is this only for large enterprises?
No. Mid-size companies deploying agents benefit most from getting governance right early — it becomes an enabler, not a tax. We right-size it to your estate.
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