Know what can act
Register agents, models, tools, workflows, identities, and lifecycle state in one governed inventory.
Agent operations, under control
Vedti Enterprise
AI Control Plane.
Vedti governs AI agents working across your most sensitive systems. Enforce runtime policy, require human approval, control MCP tools, and retain evidence for every consequential action.
Built for regulated workHuman-in-the-loop by design
RUN_0214Clinical OpsHIGH ASSURANCE
Protocol agentEvidence synthesis
›Policy checkWrite requires review
›Human approvalAssigned · D. Shah
EVIDENCE PACKETELN writeback approval
↗Project entitlement · source provenance · policy decision · approval record
THE VEDTI PLATFORM
Agents create value when they can act. Vedti makes that action governable.
One enterprise AI governance layer connects every agent, MCP tool, policy, approval, and outcome—so teams can move from experimentation to accountable execution.
Set the limits
Evaluate deterministic policy before each tool call. Default to denial when context or approval is missing.
Prove the outcome
Retain a traceable record of the action, source, rule, decision, approver, and downstream writeback.
VEDTI ASSURANCE
From agent trace
to trusted proof.
Every consequential action produces a structured evidence packet. Your reviewers see the exact context they need to approve, reject, or contain an agent action with confidence.
Explore Vedti Assurance →ASSURANCE PACKET · RUN_0214● VERIFIED
Clinical protocol deviation triageProposed action: Draft quality event in ELN
IdentityClinical Ops / Priya MehtaVerified
Policy decisionGxP writeback requires reviewReview required
Evidence & provenance6 approved sources · confidence 0.93Complete
Review assignmentQuality lead / Daniel ShahPending
Review decisionTrace ID: VT-81B4-21
START WHERE CONTROL MATTERS MOST
Built for consequential work.
Vedti gives regulated teams a practical path to adopt agentic systems without letting governance become a bottleneck.
Protect discovery. Speed up decisions.
Control agents working across research evidence, assays, ELN records, and project data—without compromising IP, provenance, or review requirements.
- Project-scoped access
- Source-linked evidence
- Controlled ELN writeback
Automate with a clear chain of command.
Let support, operations, and knowledge agents reach into enterprise systems while keeping their scope, spend, and impact visible.
- Tool-level permissions
- Approval escalation
- Live containment
CONTROL PLANE INSIGHTS
Governance briefs for teams putting agents into real workflows.
Agentic AI becomes enterprise software when every tool call, approval, writeback, and audit trail has an accountable operating model. These sections explain the architecture Vedti is built around: action with control, speed with proof.
6 governance briefs3 practical controls per brief1 operating layer
Enterprise AI Control Plane
What is an Enterprise AI Control Plane?
An enterprise AI control plane is the operating layer that governs agents, models, tools, workflows, identities, approvals, and evidence from one place. It does not replace the systems where work happens. It decides who can act, what they can access, when review is required, and how every consequential action is recorded.
Agent inventoryRuntime policyAudit evidence
Deployment Guardrails
Why AI Agents Need Guardrails Before Enterprise Deployment
Agents can search, decide, call tools, route work, and propose changes. Guardrails must evaluate the live context before those actions happen: user role, data sensitivity, business impact, system scope, and whether the action should proceed, pause for approval, or be blocked.
Least privilegeApproval triggersContainment
MCP Governance
How MCP Tools Change Enterprise AI Governance
MCP makes agents operators, not just responders. Once an agent can query records, retrieve documents, create drafts, or update workflows, tool definitions, credentials, scopes, inputs, outputs, and write permissions become first-class governance surfaces.
Tool registryCall inspectionUsage trace
Regulated R&D
Agentic Workflows in Regulated R&D: Risks and Controls
In R&D, agents can accelerate evidence review, assay interpretation, protocol drafting, literature synthesis, and candidate triage across Benchling, ELNs, LIMS, warehouses, and document repositories. The control layer must enforce project scope, provenance, lineage, and review boundaries.
Project entitlementSource provenanceStage gates
Human Approval
Human-in-the-loop Approval for AI Agents: Practical Architecture
Human review works when it is part of runtime execution. The agent proposes an action; the control plane evaluates policy, assembles the evidence packet, routes the decision, pauses execution, and releases only the approved tool call or writeback.
Evidence packetReviewer routingApproval record
Controlled Writeback
Controlled Writeback: The Missing Layer in Enterprise AI Agents
Many pilots stay read-only because enterprises are rightly cautious about AI changing operational systems. Controlled writeback creates a path between passive copilots and unchecked automation: read, draft, approve, execute, verify, and attach the result to the trace.
Draft firstScoped executionVerified update
FROM IDEA TO OPERATIONS
Built to make agent work governable.
Vedti connects the moving parts that usually live in separate conversations: agent creation, workflow orchestration, trusted enterprise connectors, policy controls, operational insight, and deployment management.
Build agents with defined ownership.Connect systems with controlled permissions.Apply guardrails before action.Deploy with visibility and evidence.
QUESTIONS, ANSWERED
Control without slowing down.
What is Vedti?
Vedti is a runtime control plane for enterprise AI agents. It governs the permissions, tools, approvals, evidence, and lifecycle around the actions agents take in your systems.
How is Vedti different from an AI dashboard?
Dashboards tell you what happened. Vedti also makes a decision before an agent can act, creates a trace of that decision, and gives authorized people the ability to approve or contain the action.
Where does Vedti fit in our stack?
Vedti sits between agents and the systems they can access. It complements your identity, data, workflow, and AI infrastructure rather than replacing them.