Service boundaries drawn from how the code behaves, not a whiteboard guess.
An API-first redesign derived from the real dependency map: what actually calls what, and what actually shares data.
- Weeks to hoursTo deploy, after the refactor to cloud-native
- 75%Lower token spend, with persistent context
- 100%Of work orders traceable end to end
- ZeroCycles spent rediscovering service boundaries
Sources needed
Four ways decomposition projects stall.
Tangled dependencies
Nobody has a real map of what calls what, only the documentation, which is out of date.
Dependency graph
Shared database
Domains that should be independent all read and write the same tables.
Living Specs
All-or-nothing deploys
A one-line change means redeploying the entire application.
Bounded Work Orders
No clear ownership
Without service boundaries, every team touches every part of the codebase.
Guardrails
Monolith to microservices, in four passes.
Map the dependency graph
A deterministic graph of how the monolith actually calls itself and moves data.
Draft service boundaries
Boundaries proposed from the real graph, agreed as the target architecture.
Guarded extraction
Each service extracted as a bounded Work Order, with drift from the target blocked at the gate.
Ship with evidence
Each cut service ships with the record of what changed and who approved it.
Seven months of scope, delivered in one week.
Senao Wireless
Cloud to on-prem Kubernetes conversion
- Speed
- 7 months1 week
- Cost
- Token spend60% lower
- Business impact
- Saved~$350K
Other modernization paths
Pick one monolith. We'll show you where the boundaries actually are.
We map the real dependency graph, propose service boundaries, and hand back the specs.