Performance Enterprise
Get more execution from the resources you already have.
Coordinate people, AI agents, projects and real capacity in one execution system — from plan to actual result.
Performance determines what should happen next, routes work to the right human or agent, tracks what actually happened, and replans from reality.
For operations, PMO and transformation leaders in companies of 200–2,000 people.
The execution loop
Performance
- 01Plan
- 02Allocate
- 03Act
- 04Measure actual
- 05Replan
Your company has plans. It doesn't have one view of execution.
Projects live in project-management tools. Meetings create new commitments. Employees have limited capacity. AI agents operate in separate systems. Managers manually collect status updates to understand what is actually happening.
Performance connects these layers into one execution loop.
01
Plans don't reflect real capacity.
02
Tasks don't show what people actually spent time on.
03
Cross-project dependencies surface after they become blockers.
04
AI agents add capacity, but create another coordination problem.
The execution loop
From plan to fact — then back into the next plan.
- 01
Plan
Projects, milestones, owners, tasks and dependencies define what should happen.
- 02
Capacity
Performance sees how much human and agent capacity is actually available.
- 03
Best Next Action
The system determines what should be executed next under current constraints.
- 04
Execution
Work is routed to the human or AI agent best positioned to execute it.
- 05
Actual
Performance records what was completed, delayed, partially completed or changed.
- 06
Replan
The next plan adapts to what actually happened.
Every cycle feeds the next plan
One workload. Human and AI capacity.
A task should not automatically consume employee time just because it exists in a project plan.
Performance evaluates who or what can execute the work and coordinates human employees and AI agents inside the same operational model.
Give machines the work machines can do. Preserve human capacity for the work that requires humans.
Performance can compare the economic cost of employee time with agent/token execution and use that information when allocating work.
Task
Performance
Yes ↓
AI agent
No ↓
Human
Hybrid ↓
Agent prepares
→Human decides
Stop planning with capacity you don't have.
A project plan is meaningless if the people assigned to it don't have the hours to execute it.
Performance connects project commitments to the real weekly capacity of every participant.
See allocation before overload becomes delay.
- →Detect overload before deadlines slip.
- →See where capacity actually exists.
- →Allocate people across competing projects.
- →Add AI capacity without losing operational visibility.
Employee A · 40h available
Performance
Project Alpha
18h
Project Beta
12h
Operations
6h
Remaining
4h
Research agent · 60 runs / week
Performance
Draft reports
24h
Ticket triage
20h
Unallocated
16h
Turn strategy into an executable roadmap.
Define the result. Break it into milestones. Assign owners. Generate or add the required tasks. Estimate the work. Connect dependencies. Then execute against the roadmap.
M1
- Owner
- Anna K.
- Tasks
- 8 / 8
- Est. hours
- 46h
- Depends on
- —
- Status
- Done
Actual progress
M2
- Owner
- Leo M.
- Tasks
- 5 / 11
- Est. hours
- 72h
- Depends on
- M1
- Status
- In progress
Actual progress
M3
- Owner
- Ria S.
- Tasks
- 0 / 9
- Est. hours
- 58h
- Depends on
- M2
- Status
- Not started
Actual progress
Project A / Milestone 3
↓ Blocks
Project B / Milestone 1
See dependencies across projects before one team's delay becomes another team's surprise.
Gantt · Dependencies
Performance
Priority isn't enough. Work has an order.
Traditional task systems tell teams what is important. Performance determines what can and should happen next.
Dependencies, deadlines, available capacity and current context continuously change the correct order of execution.
Performance turns a backlog into a dynamic execution sequence.
Dynamic Task Order
Performance
- #1Finalize specification
- #2Agent generates implementation
- #3Engineering review
- #4Deploy
- #5Measure result
Dynamic Task Order — A continuously updated order of what should be executed next.
Every participant should know what to do next.
Plans only create value when they become actions.
Performance uses current projects, dependencies, deadlines, capacity and execution state to surface the Best Next Action for the person or agent that can move the work forward.
Less time deciding what to work on. Less work waiting without an owner. Faster movement through dependencies.
Best Next Action
Performance
Review enterprise pilot proposal
Why now
- ✓Blocks customer response
- ✓Owner available now
- ✓Prerequisite complete
- ✓35 min estimated
Your plan is a hypothesis. Execution is the evidence.
Most project systems preserve the plan and ask people to update status manually.
Performance is designed to preserve both sides: what was supposed to happen and what actually happened.
Every execution cycle creates better information for the next one.
Plan
Performance
Project Alpha
- 40 planned hours
- Milestone due Friday
- 12 tasks planned
Actual
Performance
Project Alpha
- 51 actual hours
- Milestone delayed
- 9 completed · 2 moved · 1 blocked
- Plan
- Execution
- Fact
- Delta
- New plan
A meeting should change the plan.
Meeting notes are useful only if decisions become coordinated execution.
Performance can turn agreed decisions into owners, tasks and changes to the execution plan — with human confirmation where required.
The meeting ends. The operational state changes with it.
- Meeting
- Decision
- Owner
- Task / milestone
- Time / capacity
- Execution
- Fact
Replanning without silently rewriting people's commitments.
When priorities change, Performance can propose a new allocation or sequence and let the affected participant accept, modify or reject the change.
AI proposes. Humans remain part of the agreement.
Performance proposes
Performance
Move Customer Research
Tuesday 2 PM→Wednesday 10 AM
Reason: Enterprise pilot became blocking priority.
AI that doesn't wait for someone to ask the right question.
When the execution state changes, Performance can identify who needs to know and initiate the interaction.
Move coordination from manual status checking toward event-driven execution.
Milestone A slipped. Milestone B is now at risk.
Sarah is overloaded by 11 hours next week.
This task no longer requires employee time; an agent can execute it.
The prerequisite is complete. The next task can start.
Don't make the company start from zero.
Performance should sit across the tools where work already exists.
Import existing context, analyze the operating structure, and build the execution model with the team instead of forcing a blank-slate setup.
- ChatGPT / Claude exportLive
- NotionLive
- Agent systems (MCP)In development
- JiraPlanned
- AsanaPlanned
- monday.comPlanned
- CalendarsPlanned
- MeetingsPlanned
Start with one question, not a month of configuration.
Performance onboarding should begin with the operational problem the leader needs solved.
First question
What result does this team need to achieve?
- Existing context
- Projects
- People
- Milestones
- Capacity
- Execution model
AI can help reconstruct the operating context from existing systems and then ask the team to confirm it.
Your operation shouldn't have to behave like our template.
Different teams have different workflows, roles, indicators and approval structures.
Performance Enterprise is designed to adapt the execution model to the operating system of the team.
Pilot
Prove it on one real workflow.
Start with one team, one operational workflow and measurable baseline.
- Team
- 20–100 participants
- Workflow
- One real cross-functional process
- Period
- 4–8 weeks
- Baseline
- Current coordination cost, delays, capacity, plan vs fact
What we measure
- ·Manager hours spent collecting status
- ·Overloaded capacity detected before delay
- ·Tasks waiting without an actionable owner
- ·Time between deviation and detection
- ·Plan vs actual
- ·Work shifted from employees to AI agents
- ·Throughput, where measurable
The pilot hypothesis: measure how much useful execution capacity increases with the same team.
- Baseline
- Actual result
- Decide whether to expand
Request a pilot
Tell us about the team and workflow. The founder reads every request and replies personally.
Prefer email? enterprise@holisticintelligence.co