How it works:

Most project plans fail for one simple reason: they’re built around an ideal world. People are assumed to be available, tasks are treated as equal units, and deadlines are set before anyone understands real capacity. Deepleex takes a different route. It starts from reality — your team, your workload, your constraints — and turns requirements into an executable plan with transparent dates and balanced workload.

The workflow is intentionally simple. Four steps, end to end: form the team, define the work, run AI planning, execute and control.

Create your team

A plan is only as realistic as the team behind it. In Deepleex, a team is not just a list of people — it’s a working capacity model: who participates, what each person is good at, when they are available, and how fast they can deliver. This is what makes planning grounded and timelines trustworthy.

Create team
Create a team for the project (or for a separate workstream). In Deepleex, the team becomes the core planning unit: workload distribution, task sequencing, and dates are built around it.

Add or invite people
Add team members manually or invite them. Each person is treated as an individual resource — not generic “headcount” — which makes workload and availability transparent.

Assign profile and skills
Define each participant’s profile and skill set so Deepleex understands who can handle what type of work. This prevents misassignment, reduces bottlenecks, and keeps execution aligned with actual competencies.

Define working hours / schedule
Set working days, hours, and availability. Deepleex uses schedules to calculate realistic deadlines and avoid planning work into time that doesn’t exist.

Enter team productivity rate
Set productivity for the team (or participants if applicable). This is the baseline coefficient Deepleex uses to convert effort into realistic duration — so estimates match the team’s real speed, not an idealized one.

Define the work

Once capacity is clear, you define what needs to be delivered. Deepleex keeps structure and context connected: requirements become tasks and work items, and everything remains traceable back to the original goal.

Add project sections
Create sections to structure the project logically — by modules, areas, milestones, or workstreams. This keeps large scopes readable and manageable.

Enter requirements (what needs to be delivered)
Capture requirements as the single source of truth: client deliverables, business goals, internal initiatives. Requirements stay centralized and visible.

Break them down into tasks and work items
Decompose requirements into actionable tasks and smaller work items that can be estimated and executed without ambiguity.

Distribute requirements into stages
Place requirements into stages to reflect delivery phases. This helps form a clear roadmap and makes planning aligned with step-by-step delivery.

Set effort estimates and priority
Provide effort estimates and priority. These parameters define execution order and are key inputs for planning: what goes first, what is critical, and how workload should be balanced.

AI planning and launching

This is where Deepleex turns your structured scope into a working plan that accounts for skills, schedules, and real capacity — not assumptions.

Build the plan (AI planning)
Run AI planning to generate a realistic timeline and workload distribution based on your requirements, task structure, estimates, priorities, and team capacity.

Review dates and workload
Inspect results: dates, sequence, and allocation across the team. You immediately see overload, thin buffers, and risk points — before work starts.

Confirm and launch the plan
Approve the plan and launch it into execution. From this moment, Deepleex treats it as the baseline: progress, shifts, and risks are measured against the confirmed plan.

Execution & control

Execution shouldn’t rely on manual chasing. Deepleex keeps work moving, tracks deviations as they happen, and signals issues early.

Move tasks through Kanban statuses
Team members work from the Kanban flow and move tasks through statuses. The board reflects the actual project state without manual reporting.

Mark progress and completion
Update progress and completion as work happens. This builds objective execution data — not “we’re almost done.”

Track workload and schedule shifts
As execution evolves, Deepleex reflects changes in workload and timelines so you can see what’s drifting, what’s stable, and what requires intervention.

Act on “Needs attention” alerts
When something goes off track (overload, deadline risk, blockers, dependency issues), Deepleex generates a “Needs attention” alert. This is the early-warning layer that helps you correct problems while they’re still small.

Discuss in Telegram
Discuss work where the team already communicates. Deepleex supports discussion in Telegram to resolve questions faster and keep coordination close to execution.