Anuvia

Anuvia AI · Strategy · Anchor offering

AI Readiness
Sprint.

Two to three weeks producing a scored inventory of 8-15 candidate AI use cases for your operation. Each case rated on data readiness, estimated inference cost, latency budget, applicable compliance (LGPD, GxP, SOC 2, BACEN), and build-vs-buy posture. Cases that fail viability checks get an explicit no-go with reasons.

2-3 weeks · US$ 5-8k · scored use case inventory + ROI model with explicit assumptions + 12-month roadmap

15+ years inside hyperscalers · Ex-AWS · Ex-Google · Ex-MongoDB · 15× AWS-certified · MongoDB-certified · GCP-certified

What we deliver

  • Use case inventory. We surface 8-15 candidate opportunities in your business, classified by potential value and technical maturity required.
  • Viability filter. Each case gets an honest technical assessment: data availability, estimated inference cost, acceptable latency, applicable compliance rules.
  • Estimated ROI per case. Financial model with explicit assumptions. You know exactly where the numbers come from.
  • 12-month roadmap. Sequencing prioritized by impact/effort, with clear evolution gates (discovery → PoV → production).
  • Build vs. buy decision. For each prioritized case: use existing SaaS, build custom, or wait for maturity.
  • Executive presentation. Material ready for a conversation with board or technical leadership.

Why this format

Most companies start AI through experimentation — an isolated PoC that doesn't scale, or a chatbot that generates tickets instead of closing them. The Readiness Sprint inverts that order: first map where AI has a real business case, then design the execution path.

The delivery is technical, not commercial. If three of the five investigated cases don't justify the investment, we say so — and point to the ones that do. The goal is to avoid spending US$ 40-60k on projects that turn into a demo screenshot and never reach production.

The final deliverable isn't a sales deck. It's the basis on which you decide how much to invest and which case to start with.

Interactive diagnostic

Answer 4 questions. See your preliminary read.

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Sprint coverage

The three pillars we evaluate.

Strategy

Where AI generates real value in your business, separated from marketing pitch. Use case discovery, business case and prioritization by effort/impact.

Engineering

Technical viability of each case: data, infrastructure, models, integration, acceptable latency. Production-grade from the design.

Operations

AI FinOps: cost per inference, monitoring, eval harness, rollback. The path between PoC and sustainable operation at scale.

Download sample report (PDF, watermarked)

Next steps after the Sprint.

A typical client decides, based on the roadmap, whether to build a priority case in a dedicated sprint, set up a multi-agent platform, or contract a retainer for continuous follow-up. No mandatory commitment.

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