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1. Scenario

For AI product teams, algorithm engineering teams and innovation units: a standardised delivery framework from requirement insight, algorithm selection and data preparation to model development, engineering deployment and live operations. Built-in structured milestones, requirement groups, task trees with estimated workhours, test cases and document templates turn key gates — requirement sign-off, algorithm feasibility review, data audit, model acceptance and post-launch validation — into process checkpoints, so the team delivers to spec by following the sequence.

Suitable for

AI product teamsAlgorithm engineering teamsInnovation unitsProject managers who need a standardised AI delivery process

Solves

AI use cases and target outcomes are unclear, so the business sees the result as off-targetTraining data, labelling standards and acceptance criteria are not coordinatedModel development and engineering deployment fall out of step, delaying launchModel metrics and business metrics are not aligned, so value cannot be proven after launchProduct, algorithm, data, backend and operations tasks are flattened together, blurring ownership

2. Demo Company

Demo company
An AI technology company (product innovation centre)
Demo project
Smart customer-service assistant V2.0 development project

Template screenshotsClick to enlarge

End-to-End AI Product Development Screenshots 1

3. Project Template

Pre-built tasks for the whole AI product development process, requirement groups, test cases, test plans, issue tracking, interface documents and project document links. Stages are split by milestone, tasks carry workhour estimation baselines and key gates act as process checkpoints, so it works directly as a scheduling and cost reference.

Project stages
  1. 1
    Requirement insight and use-case definition
  2. 2
    Algorithm feasibility assessment
  3. 3
    Data preparation and labelling
  4. 4
    Model development and training
  5. 5
    Model acceptance and tuning
  6. 6
    Engineering deployment and integration
  7. 7
    Live operations and outcome validation

4. Custom Fields

FieldType
Task typeStatus
Estimated workhoursNumber
Model versionText
Data versionText
OwnerPerson
PriorityStatus

5. Workflow Configuration

Status
Not started→In progress→Pending acceptance→Done→Delayed→Cancelled

6. Default Document Templates

Once the template is enabled, the following document structure is generated automatically (one-click creation will be available later).

  • Project overviewProject background / target scenario / delivery scope / contacts
  • PRD (requirement document)Feature list / business flow / algorithm requirements / acceptance criteria
  • Algorithm designModel selection / training plan / evaluation metrics / risk notes
  • Data guidelinesData collection / cleaning / labelling rules / version management
  • Test planUnit testing / model acceptance / integration testing / canary release
  • Launch acceptance reportLaunch metrics / outcome validation / issue log / next steps