How can we help?

Connect GitHub, activate repositories, follow the backfill, and review your first scores.

Install the GitHub App with the repository permissions FeatureFactory needs.

Activate the repositories that should contribute to delivery metrics and scoring.

Track the initial history import, ongoing synchronization, and recoverable failures.

Open the evidence behind quality, effort, velocity, and AI attribution.

Choose attribution signals and understand known, estimated, mixed, and unknown work.

Invite teammates and give each person the minimum access their work requires.

Understand trial status, plan limits, seats, invoices, and upgrade paths.

Resolve installation, repository, import, identity, and scoring problems.

Use the command center to find attention items and follow shipped work to its intended result.

Use delivery, quality, and AI adoption signals without turning metrics into quotas.

Read durable throughput trends alongside quality and rework context.

Compare AI-assisted contribution with quality, delivery, and attribution confidence.

Map contributors to teams and compare delivery systems with appropriate context.

See how velocity, effort, and quality scores are calculated and audited.

Compare internal trends with benchmark bands while preserving scope and confidence.

Understand known, estimated, mixed, and unknown AI authorship signals.

Review your own pull requests, delivery trends, and attribution evidence.

Connect delivery activity to deployments, releases, and operational movement.

Create repeatable engineering reports and export permitted metric data.

Compare repositories after normalizing scope, ownership, and delivery context.

Manage exclusions and safely reprocess scores after a configuration change.

Follow customer evidence from ingestion through a measured product outcome.

Review source evidence, extract insights, and group recurring customer needs.

Turn a validated theme into a scoped, source-cited plan ready for delivery.

Create a work order, choose execution policy, and monitor a controlled Build run.

Bring customer and product evidence into Plan with traceable source context.

Coordinate plans with Jira work and group delivery under measurable initiatives.

Combine customer evidence, requests, usage, and health into one account view.

Resolve account identities and refresh customer context from connected systems.

Define customer tiers and track normalized requests across account evidence.

Learn about workflows, gates, approvals, and isolated cloud execution.

Execute work orders on your own machine with your environment and credentials.

Classify incoming signals and route them through human review.

Store, embed, and retrieve team knowledge for AI-assisted work.

Create execution-ready work from a plan and manage its delivery state.

Apply runner policy, review approvals, and recover failed or cancelled Build runs.

Define test coverage, review revisions, and record QA completion for delivery work.

Create classification policy and resolve incoming work through human review.

Discover product knowledge, maintain the feature catalog, and publish searchable pages.

Browse authentication, abilities, endpoints, schemas, and examples.

Send normalized source records, authenticate safely, and process webhook outcomes.

Review additive changes, deprecations, and versioning policy.

Interpret common states and choose the right recovery guide before contacting support.

Connect a provider, select resources, monitor health, and recover synchronization.

Configure engineering and work-tracking providers with intentional project scope.

Connect collaboration and customer systems while limiting ingestion to useful sources.

Manage organization details, teams, roles, and lifecycle communication preferences.

Control API credentials, account security, data retention, and organization exports.