Agentic DevOps that works
perform DevOps tasks and execute SDLC
workflows autonomously led by human engineers.
We make it work:
- From coding assistants to dev agents (human-assisted instead AI-assisted)
- From vibe coding to spec-driven coding
- From low coding to citizen-user app builders with pro coder control
- From code generation to end-to-end SDLC automation
DevOps
automation areas
Agentic solutions that work are specific to your functional domains, tech stack, solution design and operations standards.
We re-use proven AI powered SDLC setups for your type of DevOps automation objectives, among others:
- Frontend application generation
- Spec-driven backend-logic generation
- AI powered custom legacy renewal
- Agentic incident handling and patching
- Agentic quality review and continuous control / QualOps
- AI powered CI/CD and test automation
- AI powered data migration
- Citizen-user AI agent builders
- AI knowledge base curation
Transformation Path
We deeply engage with your demand,
build and run organization to
change your way of working and
enable your people.
To make AI work for you and produce P&L impact at scale, a transformation program is required:
- AI first IT Strategy for agentic DevOps
- Build DevOps knowledge bases and agentic QualOps for target/legacy systems
- System evaluation and AI driven implementation planning
- Agentic DevOps capability setup and scaling
- Agentic DevOps pioneering for individual target/legacy systems
- Scaled agentic DevOps
- SDLC Agents Operations & Quality Management
- Value Control & Optimization
Reference Use Case
Agentic QualOps Workforce
Use Case Context
Go-live of new core system with 145,000 lines of code across 2,800 files.
Use Case Value
Ensure sufficient code quality for successful go-live with large gaps in test coverage, fully identify all critical issues within hours instead of weeks, fix issues in seconds instead of hours.
Use Case Design
Run check of full codebase, identify and evaluate issues, groom issue resolution backlog and generate spec for fixing by coding agents, ongoing review of merge requests.
AI Challenge
Large fragmented codebase, 18 different Angular feature libraries, custom architecture decision records, wipe out hallucination and false positives, restrict false negatives to human expert levels.
AI Solution
EggAI de-/codification agent solution, customized to a QualOps agent orchestrating specialized review agents, coding agents for fix suggestions, classification & report generation agents, markdown file & backlog writing agent, ticketing agent, threshold agent, and coding agents for applying fixes.
AI Platform
EggAI multi-agent platform with composable open source stack on Kubernetes, deployed on Azure.
Go-To-Production
Two two-week sprints incl. platform setup, customer dev team training, and actual fixing.
Value Generation Path
Apply to other systems/code bases, integrate into day-to-day work of all teams per pull on merge, train and enable dev teams to extend QualOps solution to specific maintenance and development use cases, e.g. migration to new state management technology.
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