Designing the AI transformation roadmap for a 200-person SaaS business
A scaling SaaS company needed to make significant AI infrastructure investments but lacked the internal expertise to prioritise and sequence them. We designed their full 14-month roadmap.
Vectara Group
3×Projected ROI over 3 yearsThe challenge
Vectara Group's executive team had committed to an AI-first product strategy but had no internal framework for evaluating initiatives, sequencing investments, or building the organisational capability to execute. A previous attempt to hire a Chief AI Officer had stalled. They were at risk of significant capital misallocation in a competitive market.
Our approach
We conducted a 6-week discovery and roadmapping engagement: an AI readiness assessment across product, engineering, data infrastructure, and team capability; independent evaluation of 14 candidate initiatives against a custom prioritisation framework; business case development for the top-tier initiatives; and a board-ready roadmap presentation with sequencing rationale, resourcing model, and success metrics.
Deliverables
- —AI readiness assessment report (data infrastructure, team capability, tooling)
- —Initiative evaluation framework and scoring matrix
- —Business cases for 5 priority initiatives
- —14-month sequenced transformation roadmap
- —Resourcing model and hiring specifications
- —Board presentation and executive briefing pack
- —Vendor evaluation shortlist for 3 initiative categories
- —Ongoing advisory retainer structure
Timeline
6 weeks discovery to board sign-off
Tools
How it was built
AI readiness assessment
We evaluated Vectara's readiness across four dimensions: data infrastructure quality and accessibility, engineering team AI capability, existing tooling and integration surface area, and leadership alignment on AI objectives. The assessment surfaced three critical dependencies that had to be resolved before any AI initiative could succeed — none of which had been identified internally.
Initiative evaluation framework
We developed a custom prioritisation matrix scoring each of the 14 candidate initiatives across six dimensions: strategic alignment, data readiness, implementation complexity, time to value, competitive differentiation, and organisational risk. The framework was designed to be used by Vectara's team independently after handoff.
Business case development
For the five highest-priority initiatives, we built detailed business cases including: baseline current-state cost analysis, projected implementation costs (internal and external), quantified benefit projections with confidence intervals, and break-even timelines. Each case was stress-tested against three scenarios.
Roadmap sequencing and board presentation
The final roadmap sequenced initiatives across four phases, with dependencies, resourcing requirements, and go/no-go decision points defined. The board presentation was designed to give non-technical directors confidence in the sequencing rationale — translating technical dependencies into business logic they could evaluate.
Before / After
Measured outcomes
Key outcomes
- Board unanimously approved the roadmap in a single session — no revisions required
- First three initiatives entered execution within 30 days of roadmap delivery
- AI readiness gaps identified and remediation underway in parallel with initiative work
- Vectara's internal team now uses the prioritisation framework independently for new initiative evaluation
We went from 14 ideas and no plan to a board-approved roadmap in six weeks. EnFlow gave us the framework to think clearly about AI — and the confidence to act on it.
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