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Policy-driven control
Define and enforce enterprise rules for security, approvals, cost, integrity, external access and other governed conditions.
Features
Enterprise capability without reducing the platform to one feature.
UnifyOps brings together the capabilities required to understand, govern, execute, verify and improve AI-enabled work. Each capability has its own role while operating under a consistent enterprise trust model.
Product interface
See the operating model in practice.
A compact view of selected UnifyOps capabilities in operation.
Enterprise foundation
Designed for organizations, not isolated AI experiments.
Capabilities are presented here at the commercial level. The underlying implementation remains deliberately abstracted from the public product story.
Tenant-aware operation
Support organizational separation, governed access and enterprise boundaries so AI-enabled work can be operated across teams and environments without collapsing control into a single shared context.
Configurable workflows
Define repeatable or adaptive ways of working with configurable stages, controls and approval points while preserving a consistent governance model.
Intent-driven development
Start from the outcome the organization wants, then translate that intent into governed planning and execution rather than forcing users to pre-author every technical step.
Enterprise intelligence
Bring relevant code, documentation, relationships, impact and organizational context into AI-enabled work so decisions are grounded in the environment in which they will operate.
Built-in evaluation
Evaluate work against defined expectations so quality, completeness and readiness can be assessed rather than inferred from model confidence alone.
Reviewer capabilities
Apply independent review capabilities where the work requires additional scrutiny, including implementation review, security review and other domain-specific assurance checks.
Models and agents
Use different models and agent systems according to task, policy, cost and enterprise need while maintaining a common operating and control model.
Evidence and traceability
Keep significant AI-enabled work inspectable through durable evidence, execution history and reviewable outcomes.
Enterprise connectivity
Connect AI-enabled work with repositories, collaboration tools, delivery systems and enterprise services without making any single integration the center of the platform.
One operating model
Capabilities should reinforce each other, not compete for the product identity.
Intelligence helps AI understand. Workflows shape execution. Governance defines authority. Evaluation and reviewers test the outcome. Evidence preserves accountability. Together they form a coherent enterprise operating model.