1. Discovery

Timing: Discovery Workshop: 3 days | Capability Scan: 1–2 weeks

At DPR Solutions Inc., precision meets personalization to clarify goals, risks, and opportunities early.

We map data, content, personas, guardrails, and workflows—ensuring GenAI use cases align with outcomes, governance, and stakeholder expectations for safe, scalable value.

• Review current apps, knowledge bases, prompts, and APIs.
• Identify risks, policy gaps, and responsible‑AI constraints.
• Gather requirements from business, IT, and compliance.
• Benchmark against industry patterns and reference designs.

• Discovery Brief.
• Prioritized Use‑Case Backlog.

2. Proof of Concept

Timing: Prototype Build: 1–2 weeks | Evaluation: 1 week

We co‑create a focused GenAI prototype that proves feasibility under real constraints.

The PoC validates model fit, grounding, safety filters, and integrations—reducing uncertainty while quantifying adoption impact, speed gains, and operating costs.

• Configure sandbox with data access and content policies.
• Select models, retrieval patterns, and metrics.
• Gather feedback from users and refine prompts.
• Benchmark results against acceptance thresholds.

• PoC Results Summary.
• Go/No‑Go Recommendation.

3. Development

Timing: MVP Sprint: 2–4 weeks | Hardening: 1 week

We implement a minimal viable GenAI solution with practical guardrails and telemetry.

This phase delivers RAG pipelines, prompt orchestration, and UX—establishing policies, observability, and CI/CD so experiences are reliable, auditable, and extensible.

• Build ingestion, embeddings, and retrieval components.
• Select orchestration, tools, and safety layers.
• Gather user feedback and iterate UX flows.
• Benchmark latency, cost, and quality across paths.

• MVP Release Notes.
• Working Prototype.

4. Quality Assurance

Timing: Test Cycle: 1–2 weeks | Remediation: 1 week

We validate accuracy, safety, and reliability before release across targeted scenarios.

Tests cover hallucination rates, policy compliance, bias controls, and resilience—ensuring production behavior is predictable, secure, and measurable end‑to‑end.

• Design tests for prompts, RAG, tools, and UX.
• Select validation datasets and thresholds.
• Gather defects and prioritize fixes.
• Benchmark metrics against service objectives.

• QA Test Report.
• Release Approval.

5. Deployment

Timing: Production Readiness: 1 week | Release: 1–3 days

We operationalize GenAI securely with governance, monitoring, and change control. Rollouts coordinate infra, policies, secrets, and analytics—minimizing risk while enabling safe scale and dependable performance for business adoption.

• Automate provisioning, policies, and secrets.
• Select rollout strategy and contingency plan.
• Gather runtime metrics for cost and quality.
• Benchmark production against targets continually.

• Production Launch Checklist.
• Rollback Plan.

6. Support

Timing: Hypercare: 2–4 weeks | Ongoing Optimization: continuous

We provide long‑term support that blends insights with agility for sustained results.

Services include monitoring, incident response, policy updates, and model lifecycle—keeping experiences stable, cost‑efficient, and aligned with evolving priorities.

• Operate with observability, guardrails, and alerts.
• Select optimization levers for quality and spend.
• Gather feedback and prioritize enhancements.
• Benchmark adoption and value against objectives.

• Operations Runbook.
• SLA Metrics.