Architecture design
Solution & Transition Architecture
A coherent architecture your delivery team can build.
Define the software or AI-enabled solution, how it fits your enterprise and the transition your team should plan. Receive the agreed designs, justified choices and a usable implementation handoff.
What you receive
The result of this engagement.
A coherent software or AI solution design and transition that your delivery team can use for implementation planning.
- The agreed software or AI solution architecture, alternatives and significant decision records.
- The selected component, data, integration, AI-workflow and operational designs, including relevant security and evaluation requirements.
- A transition roadmap and implementation handoff with assumptions, dependencies and open decisions.
The engagement
An agreed design scope. A usable handoff.
- Coverage
- The selected software or AI solution, integration and transition design modules. Agree the artefact set, design depth and implementation responsibilities.
- Inputs
- Business outcomes, constraints and a sufficient baseline from your team, a prior design or discovery. Relevant technical and business owners help validate choices.
- Completion
- The agreed architecture designs and decision rationale, with transition dependencies, assumptions and open decisions, presented through an implementation handoff.
Example handoff
From an AI capability to a usable design handoff.
An internal service assistant answers employee policy questions from approved documents. The proposed solution is read-only, uses existing access permissions and escalates when it cannot support an answer.
How should the assistant retrieve evidence, generate an answer and preserve the controls the business needs?
- AuthenticateEstablish the employee identity and permitted knowledge scope.
- RetrieveSelect authorised passages with document and version references.
- Draft and checkGenerate an answer; check the response structure and cited source identifiers.
- Respond or escalateShow the draft with source references or route uncertainty to a human owner.
Chosen architecture and trust boundaries
- Choice and rationale
- Use permission-filtered retrieval before generation so access and source freshness can be managed explicitly. Candidate models and platforms are compared and the recommendation is recorded with its alternatives; this example names no vendor.
- Access boundary
- The application derives permissions from trusted identity and enforces them before model access. The model does not decide which documents the employee may read.
- Model boundary
- Pass only the authorised source context to the approved model service. The assistant cannot change business records or call write tools.
- Answer contract
- The design identifies the answer, source references, evidence status and escalation reason. Source-ID checks alone do not establish that the cited passages support the answer; evaluation and review address that separately.
Evaluation and failure behaviour
- Access test
- An unauthorised document must not reach the model, answer or employee-visible references. Engineering supplies test identities and evidence of enforcement.
- Evidence test
- Missing or conflicting supporting passages trigger abstention or escalation. Unsupported citations must be rejected; test claim support against the agreed reference answers and review method.
- Failure path
- A retrieval or model timeout returns a controlled unavailable response and a support reference. It does not produce an apparently successful answer.
- Operational control
- Assign knowledge ownership, escalation and incident handling. Agree monitoring, permitted logging and the release evaluation criteria before rollout.
Design depth, handoff and open decisions
- Architecture artefacts
- A workflow and trust-boundary design, data and interface contract outlines, decision rationale, evaluation scenarios, failure handling and transition dependencies.
- Engineering elaboration
- Delivery teams produce implementation schemas, retrieval configuration and the evaluation harness, then run tests. Prototype code and executable test assets require explicit scope.
- Open decisions
- Confirm data classification, approved model processing, permission mapping, named operating owners and the acceptance thresholds. These must be resolved for the intended deployment.
- Client decision
- Our lead architect owns the selected architecture design and rationale. The client approves the intended use and release criteria; its delivery team implements and operates.
When this helps
Recognise the situation.
- A new software or AI-enabled capability must fit existing business processes, systems and operating responsibilities.
- An AI solution needs clear data, model or agent-workflow boundaries, integration and operating controls.
- An assessment has established the problem and the team needs a coherent design response.
- Several vendors or teams need shared interfaces, non-functional requirements and a transition direction.
How it works
Evidence appropriate to the question.
Confirm the baseline
Establish the required outcomes, current constraints, evidence and architecture decisions already made.
Design and challenge
Develop options, component, data and integration boundaries and operational qualities. For AI-enabled solutions, define the selected model or workflow architecture, evaluation requirements and controls. Test the trade-offs with owners and relevant specialists.
Prepare the handoff
Record decisions, interfaces, transition dependencies and the work needed for implementation planning.
Scope & responsibility
Agree the scope and depth. Keep the boundaries clear.
Scope of the engagement
The artefact set is selected for the decision and delivery context. Adequate discovery may come from your team or another provider.
Limits of reliance
Sparkling supplies architecture work. Client or partner teams own implementation, detailed delivery estimates, testing and operations. Specialist depth is agreed where required.
The agreed scope of the engagement sets the coverage, deliverables, responsibilities, timing and fixed fee. Any change to the scope is agreed in writing.
Relevant experience
Read the work in its actual context.
Questions
Before you book.
Do you design both software and AI-enabled solutions?
Yes. The scope follows the business capability and its system context. AI-specific data, model or agent-workflow design, evaluation requirements and operating controls are included where relevant to the agreed architecture scope.
Do we need to buy your assessment first?
No. A sufficient and trustworthy baseline can come from an existing team, design or external discovery.
How long does it take?
Usually two to four weeks, longer for a large or complex change. We agree the timing and a fixed fee before work starts.
Related work
Related services
Each is available as a standalone service when the evidence and scope support it.
What's the decision in front of you?
Tell us the situation and what you intend to commit to. 25 minutes on Teams, no preparation needed. If this scope is not the right fit, we will say so.