01
Define the practical path
before you build.
Architecture, delivery model, risks, controls, and success criteria, agreed up front. Advisory gives AI and modernization work a path from proof to production.
What advisory covers.
AI strategy and readiness
Where AI belongs in your business and what your environment needs to carry it.
Agentic Delivery Readiness Assessment
A defined starting point, described below.
Architecture advisory
Target architecture and the decisions behind it.
Modernization assessments
A practical view of what to modernize, and in what order.
Cloud strategy
A cloud direction tied to workloads and outcomes.
AI DLC transformation
AI across the software delivery lifecycle, not only coding.
Governance and security planning
Identity, policy, approvals, and evidence defined early.
Proof point definition and success criteria
What success looks like, measured against your baseline.
Technology roadmaps
A sequenced path from where you are to where you are going.
Productized advisory offer
Agentic Delivery Readiness Assessment
A defined advisory entry point that helps you determine whether your software delivery environment is ready for increasing levels of AI-generated and agent-initiated change.
What we assess
1 · Engineering and SDLC maturity2 · Cloud and platform readiness3 · AI and MCP integration readiness4 · Security, identity, agent governance, and human oversight5 · Observability, evidence, outcome measurement, and operational cost
What you receive
02
Delivery and governance gaps
03
Risk and control requirements
04
Target architecture
05
Candidate pilot or proof point
06
Success measures
07
Implementation roadmap
Assess agentic delivery readinessLeads into architecture, proof of value, implementation, modernization, service delivery, or a dedicated team.
Bring us a business or technology problem.
Advisory, delivery, or dedicated engineering capacity. Start with the problem.