Our offers · Diagnostic
Data & AI Diagnostic
Eight days to gauge your data and AI maturity, frame the priorities and leave with a roadmap by horizon, before committing to any rollout.
Born from four recurring observations in the field.
Maturity that is hard to pin down
Companies struggle to gauge their real data & AI maturity against their practices, their architecture and their market.
Fragile data foundations
Without solid data quality, governance and architecture, AI projects fail to move from prototype to production.
Uncertain scale-up
Beyond the POC, companies lack a clear strategy to industrialise their AI projects and measure the ROI.
An organisation still to build
Target resources, skills and governance often remain undefined to carry the roadmap over time.
Our approach to the diagnostic
Two types of workshop
Five pillars assessed
A roadmap by horizon
A target organisation
The 5 pillars of the diagnostic
Data & AI maturity
Position the company in the light of its practices, its architecture and its market.
Data foundations
Audit the data that underpins AI projects and identify business opportunities (ROI).
AI projects
Review existing AI projects and set a scale-up strategy with the associated ROI.
Roadmap
POC in the short term, foundations in the mid term, AI expansion in the long term.
Resources & organisation
Target skills and organisation to deliver the roadmap.
Business and IT workshops, the backbone of the diagnostic
Business workshop
Run by a Dataseeds consultant together with the leadership team (CxO).
- Discuss the company and its overall organisation
- Assess maturity and market positioning
- Surface business needs and pain points
- Brainstorm concrete, high-value applications
Technical / IT workshop
Run by a Dataseeds Tech Data expert together with the technical team (CTO).
- Technical diagnostic of data quality, together with the business
- Assessment of data architecture and governance
- Review of existing AI projects
- Technical feasibility study of the envisaged projects
Run hand in hand with the business teams, these workshops form the backbone of the technical data-quality diagnostic, the essential condition for reliable AI projects.
How it runs
Dataseeds delivers the diagnostic on a baseline of 8 days, scheduled across two to three months.
3 days
Business & IT workshops
Maturity, foundations, AI projects
2 days
Technical & governance diagnostic
Data quality, architecture, organisation
2 days
Building the roadmap
Short / mid / long term + ROI definition
1 day
Target organisation & wrap-up
Resources, skills, discussion
Investment
The budget is set once the scope is framed.
The diagnostic covers all 5 pillars, wrap-up included. We start with a conversation about what is at stake for you, which is how the scope gets settled.
Several packages exist depending on the scope. We discuss them together once your needs have been debriefed.
Some packages are eligible for funding, notably from BPI France.