See and control how your organization uses AI.
Employees and systems across your company are already using AI tools. This platform gives you a single layer of visibility, governance, and cost control over all of it — without changing how your teams work.
AI adoption has outpaced AI oversight.
AI is now embedded in daily work. Employees use chat assistants to draft documents and analyze data. Engineering teams call LLM APIs from production systems. Internal agents run tasks autonomously. Most organizations have no record of any of it.
What data is leaving the organization?
Sensitive information — customer records, source code, financial data — can be pasted into prompts with no detection and no audit trail.
Who is using what, and for what purpose?
Usage is fragmented across dozens of tools, accounts, and teams, with no central inventory.
What is it costing?
AI spend accumulates across API keys, seats, and vendors with no unified accounting.
Can you prove compliance?
Regulators and auditors increasingly expect documented controls over AI usage. Most companies cannot produce one.
Unmanaged AI usage is not a future risk. It is a current, unmeasured one.
A unified control layer for enterprise AI usage.
The platform sits between your organization and the AI tools it uses. It logs, monitors, and organizes AI interactions across teams, applications, and providers — turning fragmented, invisible activity into a governed, auditable system.
One place to see everything
Every AI interaction — from employee chat sessions to automated API calls — is captured in a central record.
Governance without friction
Teams keep using the tools they already rely on. The platform operates as an intermediary layer, requiring minimal workflow change and no retraining.
From visibility to control
Once usage is visible, you can set policies: restrict data types, cap spend, define approved models, and enforce access rules — all from one interface.
Four products. One control layer.
Each product covers one dimension of AI governance — capture, protection, cost, and enforcement. Together they share a single event record, policy engine, and dashboard.
Ledger
Every AI interaction, on the record.
The capture layer. Chat, API, and agent activity lands in one normalized, immutable, searchable event record.
Explore Ledger → P.02Sentinel
Catch sensitive data before it leaves.
In-line detection of PII, credentials, and source code — redacted, hashed, or blocked at capture time.
Explore Sentinel → P.03Meter
Know what AI costs, down to the team.
Consolidated spend across providers, attributed to teams and cost centers — with budgets that enforce themselves.
Explore Meter → P.04Gate
Decide what's allowed. Enforce it everywhere.
Declarative, versioned policies for model access, data handling, and spend — applied uniformly to all traffic.
Explore Gate →Built for oversight at every layer.
Unified usage logging
Capture AI activity across chat assistants, LLM APIs, and internal agents, organized by user, team, and application.
CoreSensitive data detection
Automatically identify PII, credentials, source code, and confidential material in prompts before it becomes an incident.
SecurityUsage analytics by team and model
Understand who uses which models, how often, and for what workloads. Identify adoption patterns and shadow usage.
AnalyticsCost tracking and attribution
Consolidate AI spend across providers. Attribute costs to teams, projects, and cost centers with precision.
FinanceCompliance and audit logging
Maintain immutable, exportable records of AI interactions to support internal review, regulatory requirements, and audit requests.
ComplianceOperational in days, not quarters.
Connect
Integrate your AI endpoints, gateways, and tools. Deployment options fit your existing architecture — proxy, SDK, or API integration.
Monitor
AI activity across the organization begins flowing into a central log automatically. No behavior change required from end users.
Analyze
Review dashboards covering usage, cost, data exposure, and adoption trends — filterable by team, model, and time period.
Control
Define policies for data handling, model access, and spend limits. Enforce them consistently across every connected tool.
Designed for enterprise environments from the start.
The platform handles some of your organization's most sensitive telemetry. Its architecture reflects that responsibility.
Encryption everywhere
All data is encrypted in transit and at rest using current industry standards.
Role-based access control
Granular permissions ensure that administrators, auditors, and team leads see only what their role requires.
Privacy controls & redaction
Configure what is logged and how. Sensitive prompt content can be redacted, hashed, or excluded at capture time.
Built for internal deployment
Designed to operate within enterprise security boundaries, with deployment models that keep data under your control.
Least-privilege by default
The platform observes and governs AI traffic; it does not require broad access to your systems or data stores.
Your environment, your rules
Logging scope, retention windows, and redaction policy are defined by your organization — not by us.
This is not another AI assistant. It is infrastructure — the visibility and control layer underneath the AI tools your organization already uses.
This platform does not generate content, answer questions, or automate tasks. In the same way you would not run production systems without monitoring, or a network without access controls, AI usage at enterprise scale requires a governance layer. That layer is what we build.
Get visibility before you need it.
We are onboarding a limited number of organizations during early access. Each deployment is supported directly by our team to ensure a clean rollout and configuration matched to your environment. If your organization is adopting AI faster than it can govern it, we should talk.
Limited onboarding capacity · Priority given to organizations with active AI deployments