Target improvement for selected ticket types once AI-fit work, tool paths, and review rules are approved.
AI adoption for engineering teams
Approve AI use where it improves delivery
We help engineering leaders reduce risk, implement useful AI workflows, create observability, and stay aligned with company and regulatory standards.
Get in contactWhat leadership getsControl model
KPIsadoption and quality signals
Riskapproved guardrails
Measured impact
The metrics we baseline before promising impact
We do not sell a generic productivity number. We choose the right operational KPIs with you, measure the baseline, and then prove whether the approved workflows changed delivery.
Reduction target for idle review time when reviewers know what AI-assisted work must prove.
Targeted reduction in reopened tickets and repeated review comments for approved workflow categories.
Product options
Three packages for control, implementation, and enterprise compliance
Each path is designed around the decision companies usually need next: get control first, implement AI into delivery, or build enterprise-grade governance and compliance evidence.
AI Control Foundation
For engineering organizations that need to identify valuable AI use cases, reduce internal risk, and create a measurable operating model before scaling usage.
Get in contactWhat you have at the end
- Use-case portfolio with risk and value assessment
- Company guideline alignment for engineering AI usage
- Human review, security, and escalation rules
- KPI baseline for productivity, quality, and adoption
- Implementation roadmap for the first approved workflows
AI Workflow Implementation
For companies ready to implement AI into engineering workflows, developer tooling, and delivery processes without weakening quality or accountability.
Get in contactWhat you have at the end
- Implemented AI workflows for selected engineering use cases
- Tool integrations across coding, review, testing, and documentation
- Automation paths for test generation, code quality, docs, and handoffs
- Role-specific playbooks for engineers, reviewers, and managers
- Adoption reporting with workflow KPIs and improvement signals
Enterprise AI Governance & Compliance
For larger or regulated companies that need AI governance across engineering, security, legal, procurement, compliance, and audit requirements.
Get in contactWhat you have at the end
- Enterprise governance model for approved AI usage
- Risk classification and control ownership model
- EU AI Act and ISO-oriented compliance mapping
- Security, legal, procurement, and engineering alignment
- Approved tool standards, audit evidence, and reporting cadence
Package comparison
What the company can expect to have in place
OutcomeFoundationImplementationEnterprise
Improved AI use casesIncludedExpandedPortfolio-wide
Company guideline alignmentIncludedIncludedControl-owned
KPI baseline and observabilityIncludedOperationalizedGovernance reporting
AI workflows implementedRoadmapIncludedStandardized
Developer tooling integrationDecision recordIncludedTool standards
Testing, code quality, and documentation automationPrioritizedIncludedGoverned
EU AI Act and ISO-oriented compliance mappingGuidanceWorkflow-levelIncluded
Audit-ready governance evidenceEvidence planUsage evidenceIncluded
How we work
How we turn AI use into controlled engineering workflows
Diagnose & baseline
We map current AI use, identify valuable workflow candidates, and define the metrics that matter before rollout claims start.
- Use-case map
- Risk/value view
- KPI baseline
Define controls
We turn company, security, and regulatory constraints into practical rules engineers and managers can actually use.
- Guardrails
- Review rules
- Control owners
Implement workflows
We embed approved AI usage into delivery routines, developer tooling, documentation, testing, and review paths.
- Workflow playbooks
- Tooling paths
- Team enablement
Measure & transfer
We track adoption, quality, and delivery signals, then hand over a model leadership can operate after the engagement.
- KPI reporting
- Operating cadence
- Evidence pack
Talk to us
Scale AI in engineering with control.
We help define the workflows, guardrails, and proof you need.
Get in contact