Human expertise inside a managed operating model
Use AI for the repeatable work. Put capable people where judgement matters.
Virtual assistants and specialists provide the context, empathy, approvals, exception handling and accountable ownership that AI agents cannot safely own on their own.
Dedicated assistants · specialist support · managed coverage · named human ownership
AI + human workflow ownership
Live workflow
ExecutionAI + automation
ControlHuman-owned
IntelligenceMeasurable
VA20Four7 ownsRecurring execution and follow-through
Your team keepsStrategy, approvals and high-risk decisions
One operating model
Execution. Control. Intelligence.
Three connected layers keep the work moving without turning automation into another black box.
ExecutionAI agents + automation
Handle the stable, repeatable steps.
ControlHuman owners
Approve, resolve exceptions and own sensitive judgement.
IntelligenceQA + customer signals
Measure quality, workflow health and what users are telling you.
What the workflow can own
Design the human role around the parts of the workflow that should stay human.
We start with the workload, automate stable preparation where useful, then define the role around context-heavy ownership, approvals, exceptions, customer conversations and specialist judgement.
Dedicated virtual assistant
A named person owns recurring work inside your tools, builds context over time and becomes accountable for completion rather than isolated tasks.
Specialist support
Add focused execution in finance, marketing, revenue operations, customer support, design, development or another defined discipline.
Managed coverage
Coordinate several people, skills or shifts around a broader operating requirement while keeping ownership and handoffs explicit.
Human review for AI workflows
Place people at the approval, exception and quality-control points where automation needs context or judgement.
Customer-facing ownership
Use trained people for conversations that require empathy, negotiation, escalation or policy-sensitive decisions.
Process documentation & continuity
Turn recurring work into documented workflows so delivery can survive holidays, growth, role changes and future automation.
Execution + control
Automate what is stable. Keep human ownership where judgement begins.
The workflow separates repeatable execution from the moments that require a person. AI agents and automation handle stable steps; a named human owner handles judgement, approvals, exceptions and final accountability.
AI + human workflow ownershipWorkflow view
01Workload→02AI assist→03Specialist owner→04Outcome
ControlExceptions stay human-ownedOutcomeVisible and measurable
Intelligence layer
Do not just run the workflow. See how it performs.
The platform brings AI-agent and human-owner performance, Auto QA, scorecards and operational signals into one view. For customer-facing workflows, it also surfaces sentiment, pain points, feature requests and recurring conversation themes.
Explore the platform →Performance intelligenceLive platform
Create a repeatable quality layer around AI and human execution.
Measure workflow quality, completion and review performance.
See where automation needs human intervention most often.
Track completion, bottlenecks and recurring friction.
What changes
Less manual coordination. More visible execution.
Capacity matters, but the bigger gain is a workflow with clearer ownership, better handoffs and a measurable path from request to outcome.
A named owner
Recurring work has someone accountable for progress, quality, exceptions and closure.
Less management overhead
The role is built around clear handoffs, access, priorities and reporting rather than constant task-by-task direction.
Human judgement where it matters
AI can accelerate preparation while the person remains responsible for context, sensitive decisions and final output.
A workflow that can evolve
As the role settles, repeatable steps can be automated while the human scope moves toward higher-context work.
Fits your stackWorks around the systems you already use.
Google WorkspaceMicrosoft 365SlackNotionHubSpotSalesforceZendeskAsana / ClickUp / Jira
How we start
One workflow first. Prove the model, then expand.
We map the work, define what AI can execute safely, place the named human control points and launch with a contained scope before expanding.
Map
Understand the workload and current handoffs.
Design
Define AI execution, named human review and escalation.
Launch
Run the workflow inside your existing systems.
Improve
Use QA and performance signals to refine it.
Questions
Questions before you start
Clear answers before you decide whether the model fits.
Can we run a human-only workflow?+
Yes. AI is not forced into a workflow. If the work, risk profile or internal policy is better suited to a human-only process, we can operate it that way.
How do you decide whether we need a VA, specialist or automation?+
We start with the workload. Stable repeatable steps are candidates for automation; context-heavy ownership, approvals, exceptions and relationship work define the human role.
Can one person work across several functions?+
Sometimes. We scope around the actual workload and required depth. When the work needs specialist judgement, a focused role or coordinated coverage is usually stronger than forcing everything into one generalist position.
Will the assistant use AI?+
Where it helps and your policies allow it, yes. AI can assist with research, summaries, drafting, classification and repetitive preparation while the person remains responsible for review and final output.
What if the match is not right?+
We review whether the issue is the person, the scope, the workflow or onboarding and adjust the model accordingly.
Can the scope change later?+
Yes. The role should evolve as you learn which work should stay human, which can be automated and where additional capability is needed.
Start with the workload
Put the right person at the right point in the workflow.
Tell us what is still consuming human attention after the repeatable work is mapped. We will help define the right role, ownership and AI support around it.