AI Implementation / Discovery and Architecture / Decision package
What YPAI defines
Eight records, one control document. Every major decision is recorded with its rationale, assumptions, dependencies, rejected alternatives and conditions for reassessment.
Each engagement produces a decision package that product, engineering, security, legal, finance and operations teams can use to approve, build, test or reject an implementation.
Decision package
What each team receives
Product and operations
The operating workflow specification and the implementation roadmap: users, actors, triggers, inputs, decisions, outputs, exceptions, handoffs, the current baseline and the intended business outcome; the pilot boundary, production sequence, work packages and decision owners.
Engineering
The system and integration architecture, the data and knowledge readiness record and the evaluation plan: channels, identity, models, routing, context, memory, tools, APIs, events, source systems, error handling and human checkpoints; sources, permissions, quality, coverage and identified gaps; the representative task set, metrics, thresholds, graders and regression gates.
Security, legal and finance
The automation and authority boundary, the security and governance controls and the unit economics: what the system may retrieve, recommend, generate, decide, execute, approve, escalate or never perform autonomously; threat model, access boundaries, policy enforcement, logging, oversight, incident handling, rollback and change control; expected demand, model consumption, infrastructure cost, operating effort and cost per accepted outcome.
Decision-ready outputs
The package is written so that product, engineering, security, legal, finance and operations can approve, build, test or reject the implementation from the same records.
The implementation roadmap carries SOW-ready scope: work packages, dependencies, decision owners and handoff requirements.
What your team can build from
The workflow specification, architecture record, evaluation plan, control model and implementation backlog are designed to support handoff.
The architecture record can also be handed to the client’s internal team or another implementation partner.
Discovery does not require a downstream build commitment.
The boundaries
The package states what will be built and what will not. The authority boundary records what the system may never perform autonomously; the roadmap records the pilot boundary and what depends on shared infrastructure.
| Decision record | What it contains | |
|---|---|---|
| 01 | Operating workflow specification | Users, actors, triggers, inputs, decisions, outputs, exceptions, handoffs, current baseline and intended business outcome. |
| 02 | Automation and authority boundary | What the system may retrieve, recommend, generate, decide, execute, approve, escalate or never perform autonomously. |
| 03 | Data and knowledge readiness | Sources, ownership, permissions, rights, quality, coverage, structure, freshness, residency, retrieval suitability and identified gaps. |
| 04 | System and integration architecture | Channels, identity, models, routing, context, memory, tools, APIs, events, source systems, error handling and human checkpoints. |
| 05 | Evaluation and acceptance plan | Representative task set, edge cases, adverse cases, metrics, thresholds, graders, human review rules and regression gates. |
| 06 | Security and governance controls | Threat model, access boundaries, policy enforcement, logging, oversight, incident handling, rollback and change control. |
| 07 | Unit economics and capacity model | Expected demand, throughput, latency, model consumption, infrastructure cost, operating effort and cost per accepted outcome. |
| 08 | Implementation roadmap | Pilot boundary, production sequence, dependencies, work packages, decision owners, handoff requirements and SOW-ready scope. |
Every major decision is recorded with its rationale, assumptions, dependencies, rejected alternatives and conditions for reassessment.
The architecture record becomes the control document for the build.
Inspect the real operating environment.
Working sessions are used to resolve decisions and validate findings. They are not the final product.
Depending on scope, YPAI may review:
- workflow documentation and standard operating procedures
- representative cases and inputs
- existing prototypes, prompts and evaluations
- application and model logs
- data and knowledge sources
- API and integration documentation
- identity and permission models
- infrastructure and deployment requirements
- security and privacy policies
- user roles and approval structures
- workload volumes and service levels
- budget and procurement constraints
- applicable legal and sector requirements
Measure the cost of the completed work.
Token price alone does not describe whether an AI system is economically viable.
YPAI models the cost of the full operating path:
- model inference
- retrieval and storage
- tool execution
- infrastructure
- third-party services
- human review
- retries and failed runs
- monitoring and evaluation
- support and incident handling
- model and data updates
- expected volume and peak demand
The primary economic unit is tied to the workflow, such as cost per accepted document, resolved case, completed request, approved action or successful customer interaction.
Architecture alternatives are compared against both performance and cost per accepted outcome.
A cheaper model that creates more failures, review work or retries is not necessarily the lower-cost system.
Discovery and architecture
Frequently asked questions
What happens when required data is missing?
YPAI identifies the gap and specifies the collection, sourcing, annotation, curation or evaluation work needed. That work can be delivered separately through AI Data & Evaluation or connected to the implementation engagement.