Context Loses Source
Answers arrive without the document, version, or permission that produced them, so nobody can defend the result later.
Enterprise AI Governance Platform
The Enterprise Operating Layer for Accountable AI
Bring governance, provenance, execution, verification, and human review into a single AI operating system.
A working Founder Edition exists locally. Founder Edition is available for purchase.See pricing →
Governance Dashboard
LiveTasks
1,284
+12
Approved
1,196
+9
Pending
47
+3
Avg Conf
93.4%
+0.8
TaskConf.ReviewerStatus
- 96%S. ChenApproved
Q4 Earnings Summary
8 src · 2m ago
- 91%J. ParkIn Review
Contract Review #447
3 src · 5m ago
- 88%M. RodriguezApproved
Supplier Risk Assessment
5 src · 12m ago
- 99%A. KumarApproved
GDPR Compliance Audit
12 src · 1h ago
- 94%—Running
Policy Enforcement Check
2 src · now
- Governance First
- Provenance Tracking
- Human Authorization
- Verifiable Evidence
- Audit Ready
The enterprise problem
AI output is fast. Accountability is not.
Automation Outruns Policy
Agents act faster than approval paths can keep up, and policy becomes a document instead of an enforced control.
Results Lack Evidence
Output looks finished but carries no verification record, so review teams re-do the work to trust it.
The operating layer
One governed path from context to approval
Six controlled stages replace ungoverned prompting. Each stage keeps its evidence.
Connect. Approved systems and permissions are attached to the workspace.
Product ecosystem
A system architecture, not a set of features
Core
AI Workspace Core
One operating layer that carries identity, policy, provenance and evidence across every module below.
01
Assignments
Work is scoped, permissioned and traceable before it starts.
02
Execution
Agent work runs inside enforced enterprise policy.
03
Verification
Claims are checked against retrieved evidence.
04
Human Review
Reviewers see claim, source and confidence together.
05
Enterprise Decision
A named approval seals the accountable record.
See it work
Context, assignment, execution, verification, decision
A live walkthrough of how a single piece of work becomes an accountable record.
Workflow walkthrough
▸ policy-v7.pdf · supplier-master.csv · q4-ledger.xlsx
Trust
Built so an auditor can follow the work
Verified statements point to repository evidence. Design intent, demonstrations and limitations are labelled separately so a buyer can distinguish proof from direction.
Evidence retention
Sources, versions and verification records are retained with the result.
Governance workflows
Policy is enforced at execution time, not documented after the fact.
Human authorization
Consequential actions require a named person to authorise them.
Decision accountability
Every approval records who decided, on what evidence, and when.
Review checkpoints
Work stops at defined checkpoints until review is complete.
Product portfolio
One operating thesis. Clear product boundaries.
The portfolio separates the enterprise operating layer from domain-specific authorization products. Maturity is stated on every surface.
Core platformVerified foundation
AI Workspace
Organizational knowledge, governed assignments, execution, verification and review.
Explore the platformCommerce authorizationLocal sandbox demonstration
Warrant
Clause-cited ALLOW, ESCALATE or DENY decisions for AI purchasing proposals.
Explore WarrantAgent tool policyReference implementation
Warrant MCP
Deterministic checks for supported tool calls, with binding enforcement in Claude Code.
Explore Warrant MCPDomain productsNot presented as available
Evidence gate first
Future domain surfaces appear only after their repository capability and maturity boundary are accepted.
See what we are building nextEvaluate the evidence, not the promise.
Review the platform evidence, inspect the authorization products, and decide whether the current boundary matches a problem worth testing together.