Project Name
AI-Assisted Backstage Developer Self-Service Portal for a Large Enterprise
A large-scale software technology organization operating a complex, multi-cloud infrastructure estate had a platform engineering team intended to be a multiplier, building capabilities that let every developer team move faster. Instead, the team had become the manual executor for every routine developer request, handling rollbacks, IaC updates, staging environment creation, service migrations, decommissions, feature flag changes, and access requests, all routed as tickets that consumed platform capacity and introduced multi-day delays for development teams.
With no self-service capability in place, developer teams were waiting 2 to 5 days for requests with well-understood, repeatable execution paths. The platform team had no capacity left for capability development, and developer experience dissatisfaction was showing up in engineering satisfaction surveys. The organization needed a solution that would allow developers to execute routine workflows autonomously, without routing through the platform team, while maintaining governance, audit, and cost attribution. The organization partnered with Ksolves, an AI-First Company, to design and deploy an AI-assisted Backstage developer portal that enables self-service execution across 7+ workflow types, with policy guardrails, automated approval routing, and full audit and cost attribution built in.
The challenges faced by the client are as follows:
- Platform Team as Ticket Executor: A significant share of the platform team's weekly capacity was consumed by manually executing routine developer requests rather than building the platform capabilities that would compound in value over time.
- Multi-Day Lead Times for Routine Requests: Rollbacks, staging environment creation, and IaC updates, all with well-understood execution paths, were delayed by 2 to 5 days due to platform team queue depth, slowing developer velocity and release cycles.
- Inconsistent Execution Quality: Manual execution of requests by different platform engineers produced inconsistent outputs, particularly for IaC changes and RBAC configurations, creating operational variance that complicated downstream management.
- No Audit Trail or Cost Attribution: Manually executed requests generated minimal audit records and no automated cost attribution, making it difficult to track which teams were consuming which infrastructure resources and at what cost.
- Developer Experience Friction: Development teams reported self-service as a consistent source of frustration in engineering satisfaction surveys, with multi-day ticket wait times for routine operational requests cited as a significant contributor to developer experience dissatisfaction.
Ksolves, an AI-First Company, designed and deployed an AI-assisted Backstage developer portal that provides self-service execution capability for 7+ workflow types, including rollbacks, IaC updates, staging environment creation, service migrations, decommissions, feature flag management, and access provisioning, with policy guardrails, automated approval routing, and full audit and cost attribution built in.
- Backstage Self-Service Portal: Ksolves built a Backstage-based developer portal exposing software templates for all 7 common workflow types, allowing any authorized developer to initiate execution without platform team involvement.
- AI-Assisted Form Completion and Validation: Ksolves integrated AI assistance into workflow forms, suggesting parameter values based on service context, validating inputs against policy rules before submission, and flagging potential issues before execution begins.
- Policy Guardrail Engine: Ksolves built a policy evaluation layer that checks every submitted workflow request against infrastructure governance rules, including environment constraints, cost limits, and security policies, blocking non-compliant requests with clear guidance before any execution occurs.
- Automated Approval Routing: Ksolves configured intelligent approval workflows that automatically route requests requiring senior approval, such as production deployments and large resource allocations, to the correct approver, while processing low-risk requests without approval overhead.
- Audit Trail and Cost Attribution: Ksolves integrated every workflow execution with JIRA for ticket auto-creation and cost management tooling for real-time infrastructure cost attribution, providing complete traceability from developer request to infrastructure resource.
Technology Stack
| Layer | Technology |
|---|---|
| Platform | Backstage |
| Infrastructure | Terraform Cloud / Argo CD |
| AI/ML | AI Form Assistance and Validation |
| DevSecOps | GitHub Actions |
| Security | HashiCorp Vault / IAM Integration |
- Self-Service for 7+ Workflow Types: Every routine developer request was previously raised as a platform team ticket, with 2 to 5-day lead times. Rollbacks, IaC updates, staging creation, migrations, decommissions, feature flags, and access requests are now all self-served directly by developer teams through the portal.
- Platform Ticket Queue Reduced: The platform team previously spent most of its weekly capacity on routine developer requests. Self-service now handles the bulk of routine workflow execution, freeing the platform team to focus on capability development and reliability work.
- Routine Request Lead Time Cut to Minutes: Requests that previously waited 2 to 5 days in the platform team queue now execute in minutes with no dependency on platform team availability.
- Full Audit Trail and Cost Attribution Achieved: Manually executed requests previously generated minimal audit records and no automated cost attribution. Every self-service execution now automatically produces a complete audit record and real-time cost attribution.
“Our developers used to raise a ticket and wait days for things they should be able to do themselves in minutes. Now they just use the portal. The platform team is finally doing platform work.”
– Head of Developer Experience
Ksolves transformed a manual, ticket-driven platform operations model into a governed, AI-assisted self-service portal covering 7+ developer workflow types. The organization moved from multi-day lead times and platform team bottlenecks to a model where developers execute routine workflows autonomously in minutes, with full policy enforcement, automated approval routing, and complete audit and cost attribution.
The self-service model scales indefinitely. Additional developer teams and new workflow types can be onboarded without increasing the platform team’s operational load, and the organization is positioned to extend the Backstage catalog further, integrate AI-powered cost-optimization recommendations into provisioning workflows, and build an internal developer marketplace on the portal foundation.
For organizations where the platform team is still the bottleneck for routine developer requests, our AI & ML Consulting Services delivers the self-service capability, governance, and developer experience required for high-performing engineering organizations.
Is Your Platform Team Still the Bottleneck for Routine Developer Requests?
