Enterprise
Reinforce your data team with on‑demand expertise
Quick answer
This page explains how Datasive supports enterprise groups and private equity portfolios with a fractional CDO and AI agents. It outlines delivery formats, post-acquisition use cases, and concrete outcomes to accelerate value creation and reduce risk across multiple entities in the portfolio.
Focused 4–12 week task forces to solve a precise topic, without replacing your CDO. Built for enterprise groups, LBO‑backed mid‑market companies, and investment funds.
Enterprise pain points
Deliver fast decisions without compromising compliance or multi‑BU coordination.
Multi‑BU / multi‑country governance
Align standards, ownership, and decision cadence without slowing local teams.
AI Act, NIS2, DORA compliance
Pragmatic control frameworks, audit trails, and compliance reporting.
Post‑M&A rationalization
Remove stack overlap, converge models, and control costs.
Federated data operating model
Compatible with local constraints while keeping group steering.
Board‑level ROI
Decision packs, value KPIs, and a clear financial narrative for sponsors.
Shared global data platform
Avoid BU‑level silos by harmonizing the platform and data products.
Business engagement & adoption
No Shadow AI: controlled adoption with measurable business value.
Scaling data & AI
Systematically scale use cases with data & AI build‑up.
Private Equity & LBO‑backed mid‑market
A fractional CDO for your portfolio
Accelerate data & AI value creation across the portfolio — without hiring a CDO in every participation.
POST‑ACQUISITION — First 100 days
Flash data diagnostic, legacy system mapping, data integration plan.
→ Board‑validated data roadmap in 30 days
VALUE CREATION — AI acceleration
Identify and deploy AI use cases with direct P&L impact.
→ 2–3 use cases live in 6 months, measured ROI
EXIT READINESS — Pre‑sale
Data/AI data room, governance documentation, maturity KPIs for buyers.
→ Data maturity score reflected in valuation multiple
PORTFOLIO‑WIDE CDO
One CDO deployed across 2–4 participations. Unified reporting for the Operating Partner.
→ Shared cost, cross‑portfolio benchmarks
Every data action is translated into EBITDA impact. We don’t talk about “governance” or “data quality” — we talk margins, multiples, and due‑diligence risk.
Typical budget: €15,000–€25,000/month for 2–3 participations. The cost of one Big 4 consultant — for a C‑level expert who delivers, not supervises.
Why Datasive vs McKinsey, BCG, or Accenture?
Who delivers
1 partner in sales, 3-5 junior consultants in delivery
1 C-level expert who sells AND delivers. Same hands from diagnosis to execution.
What you get
A 150-slide PowerPoint deck. “Our recommendations…”
Board-ready decision packs, dashboards connected to your data, AI policy deployed.
Time to impact
6-12 months of diagnosis before any tangible deliverable.
90 days for the first 3 actionable deliverables.
Cost
€200–500K for a maturity audit + roadmap.
€14–28K for a full maturity audit + roadmap + 3 decision packs.
After the project
You keep the deck. No one executes.
AI agents remain accessible. Fractional CDO continues if needed.
Olivier Soudée
Former CDO Office Lead PwC · Head of Data Europe Nissan · Chief EA Pernod Ricard · INSEAD GEMBA
See full profile →Case study
AI governance and data rationalization after an acquisition
European group, 8,000+ employees, 4 countries. Shadow AI was endemic, 13 tools not rationalized.
47
critical data assets documented and secured
13→6
tools rationalized (−€500K/year in licenses)
100%
AI Act coverage on identified use cases
3
board-ready decision packs delivered
Ecosystem & partners
Trust signals
Engagement formats built for enterprise
Three engagement modes for group constraints: agent autonomy, executive leadership, or a dedicated task force.
AI Agents + Fractional CDO
Combine autonomous agents with strategic leadership to accelerate decisions without adding org complexity.
Full‑time intervention
Interim CDO embedded full‑time for 3–6 months to stabilize governance, prioritization, and execution.
Data & AI task force
Dedicated team on a time‑boxed topic (4–12 weeks) with board‑ready deliverables and handover.
Priority use cases for enterprise teams
High-impact examples validated in complex environments.
3-6 months
Predictive lead scoring: prioritize prospects who will close
Prioritize prospects based on their conversion probability using an ML model trained on CRM history.
See the case →
3-6 months
Sales forecasting
Predict future revenue by product/region/rep using statistical or ML models.
See the case →
3-6 months
B2B churn analysis
Identify customers at risk of churn using behavioral and transactional signals.
See the case →
Procurement‑ready
RFPs, approved panels, security/compliance requirements, and group‑level contracting. We align with your procurement standards.
Talk to an expert
We scope your need and recommend the right engagement format.
Next steps
Fast paths to keep the conversation moving.