GenAI Readiness Assessment for AWS (Bedrock & Amazon Q)

Most enterprises are now being asked to ship Generative AI features — but few have a disciplined way to choose which use cases are worth pursuing, which AWS Bedrock or Amazon Q model fits each one, what the cost and latency profile will look like at scale, and how to frame the security, privacy, and governance posture that legal and risk teams will sign off on. The result is stalled pilots, runaway spend, and shadow AI that quietly bypasses controls.

**The Ibexlabs GenAI Readiness Assessment for AWS is a three-week, structured engagement built specifically to break that deadlock. **

• We work alongside your business, data, and platform leaders to turn loosely-held GenAI ambitions into a prioritized backlog, a reference architecture grounded in Amazon Bedrock and Amazon Q, an enterprise governance and guardrails baseline, and a build roadmap with realistic cost modeling — so engineering can start shipping with confidence the day the assessment ends.

Week 1 — Discover and Frame. We run structured interviews with up to ten stakeholders across business, data, security, and platform teams to inventory candidate GenAI use cases, capture data sources, and document existing AWS estate, identity, and data-classification posture. We also benchmark organizational AI maturity against the AWS Generative AI Lens of the Well-Architected Framework.

Week 2 — Evaluate and Architect. We score each candidate use case on business value, technical feasibility, data readiness, risk, and time-to-value, then propose a target architecture pattern for the top contenders — covering model choice across Amazon Bedrock foundation models (Anthropic Claude, Amazon Nova, Meta Llama, Mistral, Cohere) and Amazon Q Business or Amazon Q Developer where appropriate. For each pattern we model token economics, latency budgets, retrieval-augmented generation (RAG) design, evaluation harness, and integration touchpoints.

Week 3 — Govern and Roadmap. We define the governance and guardrails baseline: PII handling, content filters via Amazon Bedrock Guardrails, prompt-injection defenses, audit logging via CloudTrail and CloudWatch, model-access controls, human-in-the-loop review, and an evaluation and red-teaming playbook. We close with a costed build roadmap — quarter-by-quarter sequencing, team-shape recommendations, MLOps and LLMOps tooling, and explicit success metrics for each prioritized use case.

Deliverables include:

1. A prioritized GenAI use-case backlog with scoring rubric;
2. Cost and latency model spreadsheet;
3. 12-month build roadmap with sequencing, and success metrics.

This assessment is for enterprises that have a board-level mandate to ship GenAI in the next two to four quarters, that operate on AWS or are migrating to it, and that need to align engineering, security, and the business around a single, defensible plan before committing build budget. If you have already piloted a chatbot or copilot and now need to scale responsibly, this is the engagement that turns a proof of concept into a production program.

Ibexlabs is an AWS Premier Tier Consulting Partner with 100+ AWS certifications, 8 AWS Competencies, and 11 Service Delivery Programs. We are AWS GenAI Services & AWS GenAI Software Competency Partner and have helped multiple of enterprises modernize on AWS — including end-to-end Generative AI builds on Amazon Bedrock and Amazon Q. Pricing for this assessment is delivered via private offer; request one from the listing to receive a tailored quote scoped to your environment and use-case ambitions.