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Business Solution

ISV Partners

A partner path for specialist software and agentic solutions.

ISV partners can connect specialist capability into the Advanze operating model so customers get domain depth without creating another disconnected application island.

Platform and governance team reviewing AI execution, controls and architecture.
ISV Partners starts with people trying to make the right call. Teams want to use AI more widely.

Solution / ISV Partners

A practical operating model for this environment

Advanze solutions describe how products, workflows, data, integrations and agents work together to solve an operating problem. For ISV Partners, the focus is practical transformation: reducing fragmentation, creating reliable execution paths and giving people better control over work that crosses teams and systems.

The value is strongest when the capability is connected to adjacent processes. Records, workflows, controls, communications and analytics should participate in a shared execution fabric rather than live in separate tools.

Platform and governance team reviewing AI execution, controls and architecture.
Where ISV Partners becomes real work people can trust. Platform, architecture and governance teams controlling agentic execution, cost and operational risk.

Core capabilities

What ISV Partners enables

Each capability is designed to work as part of the broader execution platform rather than as a disconnected module.

Specialist apps

Use specialist apps as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Shared data context

Use shared data context as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Reusable APIs

Use reusable apis as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Workflow handoff

Use workflow handoff as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Marketplace packaging

Use marketplace packaging as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Customer rollout

Use customer rollout as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

The Advanze Control Model - AI Agents Execute Work Inside the Control Model

Agentic operating model

AI agents execute work inside the control model

Advanze treats AI agents as participants in the operating model. Agents can read context, call services, update records, trigger workflows, prepare decisions and escalate exceptions. Human teams remain responsible for judgement, governance and business accountability.

The goal is to create an execution platform where work can move across functions with consistent permissions, policies, audit trails and data visibility.

Business outcomes

What becomes possible

Unified operating modelConnect the workflows, data and decisions that drive outcomes.
AI-enabled capacityScale work with governed agents rather than only headcount.
Modernised processReplace fragmented tools with composable services.
Clear transformation pathMove from pilot to measurable adoption through phased delivery.
Platform and governance team reviewing AI execution, controls and architecture.
The outcome is not just automation. It is confidence in what happens next. When ISV Partners runs inside a governed execution model, teams can move faster without losing judgement, accountability or trust.

Agentic use case

Where ISV Partners becomes governed execution.

Teams want to use AI more widely.

What makes it harder in the real world: The cost of enterprise AI is not only token price. It includes context packaging, orchestration, approvals, safety layers, retries, evaluations, auditability and operations support.

What Advanze changes: Control AI execution by routing tasks to the right model, setting run budgets, applying permissions, stopping loops and reporting usage by use case.

Router AgentSelects the smallest capable model or workflow path for the task.
Budget AgentTracks per-run and monthly use-case budgets.
Evaluation AgentChecks output quality, policy fit and repeated failure patterns.
Runtime Control AgentStops loops, retries safely and escalates when budget or quality thresholds are breached.
OwnerReviews value, adoption, cost and exceptions.
Challenge

The cost of enterprise AI is not only token price. It includes context packaging, orchestration, approvals, safety layers, retries, evaluations, auditability and operations support.

Orchestration

Control AI execution by routing tasks to the right model, setting run budgets, applying permissions, stopping loops and reporting usage by use case.

Success

Control AI execution by routing tasks to the right model, setting run budgets, applying permissions, stopping loops and reporting usage by use case.

Platform and governance team reviewing AI execution, controls and architecture.
AI runtime control 12Platform, architecture and governance teams controlling agentic execution, cost and operational risk.
Platform and governance team reviewing AI execution, controls and architecture.
AI runtime control 13Platform, architecture and governance teams controlling agentic execution, cost and operational risk.
Platform and governance team reviewing AI execution, controls and architecture.
AI runtime control 14Platform, architecture and governance teams controlling agentic execution, cost and operational risk.

Why AI execution needs architecture

The work needs context, controls and clear permissions before automation can safely act.

That is why the Advanze control model matters: identity, permissions, policies, workflow, audit evidence and human judgement are embedded into execution before agents act.

  • The cost of enterprise AI is not only token price. It includes context packaging, orchestration, approvals, safety layers, retries, evaluations, auditability and operations support.
  • The right agent must receive the right context, tools, permissions and approval path before work moves forward.
  • Audit evidence, exception handling and human judgement need to be part of the workflow, not notes added after the fact.

Implementation path

How to move from concept to production

Advanze can be introduced progressively. Start with a visible workflow, prove the operating model, then expand into adjacent capabilities as the platform foundation matures.

  1. 1
    Assess the current operating model

    Map workflows, systems, data sources and manual coordination points around this capability.

  2. 2
    Design the target execution flow

    Define data, approvals, agent tasks, service calls and governance controls.

  3. 3
    Launch a focused implementation wave

    Start with a bounded use case that proves the operating pattern and creates reusable platform assets.

  4. 4
    Scale across the business

    Extend the pattern to adjacent workflows, more agents, more users and deeper integrations.

Next step

Build this into your execution platform roadmap

Explore how ISV Partners can be implemented as part of a broader Advanze platform adoption programme.