AI Strategy & Roadmap
- 8 - 16 weeks to production
- Fixed-scope milestone contracts
- Dedicated senior engineer
- Weekly delivery checkpoints
- 30-day post-launch monitoring
- OpenAI, Anthropic, Cohere
- AWS Bedrock, Azure OpenAI
- LangChain, LlamaIndex
- Pinecone, Weaviate, pgvector
- Weights & Biases, MLflow
AI strategy is where most consulting engagements start — and where most of them end. A roadmap sitting in a shared drive isn't a strategy. A prioritized, scoped, resourced plan tied to specific business outcomes is. That's what Bivoxo produces, in two weeks.
What we do for clients
We work across the full AI strategy lifecycle:
- AI maturity assessment - structured evaluation of your data readiness, technical infrastructure, team capability, and organizational readiness across five dimensions
- Use-case identification and prioritization - systematic mapping of AI opportunities across your business, scored by feasibility, ROI, and time-to-value
- Build vs. buy analysis - structured framework to determine what to build custom, what to buy off-the-shelf, and what to configure from foundation models
- Implementation roadmap - a phased 12-month plan with defined milestones, resource requirements, cost projections, and risk flags
- Data readiness audit - honest assessment of whether your data can support the use cases you are considering, and what it would take to close the gaps
- Governance and compliance mapping - regulatory and security requirements identified and mapped to your roadmap before any build decisions are made
How we run an AI Strategy engagement
Every strategy engagement follows the same three-phase structure, led by a senior partner at each stage:
- Diagnose. We interview your stakeholders, audit your data, and map your existing technical environment. We are looking for two things: where AI can create measurable value, and where the assumptions that would kill an implementation already exist. This phase typically runs one to two weeks and ends with a prioritized use-case longlist and a data readiness report. We will tell you if something is not viable before it becomes a roadmap item.
- Design. We score and rank the shortlisted use cases against a consistent framework - business value, data feasibility, technical complexity, time-to-value, and organizational readiness. The output is a sequenced implementation roadmap with defined milestones, resource requirements, and a build vs. buy recommendation for each use case. You review and approve the roadmap before anything moves to implementation.
- Handoff and planning. We present the roadmap to your leadership team, walk through the assumptions behind every recommendation, and produce a scoped proposal for the first implementation phase. If you move forward with us, the strategy engagement folds directly into the Diagnose phase of the implementation. If you take it in-house or to another partner, you have everything you need to do that.
The best AI strategies don't feel like consulting deliverables. They feel like a clear answer to a question your organization has been circling for months.— Bivoxo, Our Founding Principle
Where we fit best
Every engagement is custom-scoped based on your data environment and specific requirements. We discuss typical investment ranges during our initial discovery call.
We are a particularly strong fit for:
- Organizations that have had a previous AI initiative fail or stall and need an honest assessment of why
- Leadership teams that need a defensible business case for AI investment before committing budget
- Technology and data teams that know what they want to build but need external validation and sequencing
- Companies preparing for a significant AI investment and want to de-risk the decision before contracts are signed
We work closely with your internal engineering and data teams throughout - and have a strong track record of producing strategies that internal teams can actually execute, without the friction that comes from recommendations made without understanding the existing stack.
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