01
Platform boundaries that increase team autonomy
Define stable domain and infrastructure contracts instead of centralising every decision in one platform team.
Industry / TS
Product engineering for software businesses that must scale change and trust together.
Technology companies compete through delivery velocity, but growth exposes architecture, reliability, security and cost assumptions that early products could postpone.
Operating context
Technology has to fit the institution around it.
Technology companies compete through delivery velocity, but growth exposes architecture, reliability, security and cost assumptions that early products could postpone.
The objective is a platform and operating model that lets teams ship independently while preserving shared evidence, policy and service reliability.
Operating agenda
Priorities that shape the architecture.
We translate operating risk and commercial objectives into explicit system boundaries, evidence and decision ownership.
02
AI product features with sustainable economics
Evaluate quality, latency, safety and inference cost as one product decision.
03
Reliability that grows with product complexity
Make dependency, capacity and recovery evidence part of delivery rather than an operations afterthought.
Engineering contribution
Where Root Digit contributes.
Each engagement is scoped around a real operating decision, a controlled technical boundary and evidence that leadership can review.
TS.1
Platform and product modernisation
Domain decomposition and cloud-native services around a product roadmap.
- Architecture and APIs
- Data and event platforms
- Incremental modernisation
TS.2
Developer platforms
Golden paths and delivery systems that reduce cognitive load without hiding control.
- CI/CD and environments
- Service templates and policy
- Engineering observability
TS.3
AI product engineering
Production model, retrieval, agent and evaluation systems.
- Model serving
- Retrieval and tool orchestration
- Quality and safety evaluation
TS.4
Reliability and unit economics
Service design connecting performance, cost and recovery.
- SLO and capacity engineering
- FinOps instrumentation
- Failure and recovery testing
Control plane
Controls designed with the system.
Assurance is part of the architecture and operating model—not a review added after delivery.
01
Contract ownership
Service and data contracts have owners, compatibility policy and retirement paths.
02
AI evaluation
Quality, safety, latency and cost gates run against representative workloads.
03
Supply-chain security
Dependencies, builds and artifacts remain attributable and verifiable.
04
Service recovery
Critical paths have tested rollback, failover and restoration evidence.
Practical entry points
Start with one decision that matters.
01
Decompose one scaling bottleneck
Create a bounded service around a domain blocking product or team velocity.
02
Productionise one AI workflow
Build evaluation, observability and cost controls around a real user decision.
03
Prove one recovery objective
Exercise a critical service through dependency failure and restoration.
Continue exploring
Related capabilities and evidence.
Industry conversation