episteme.work/corporate/catalog
One mandatory entry point. Four service lines. Four tiers. A coherent progression designed to match where you actually are — not where you think you are.
EP-00 Integral Maturity Diagnostic is required before any implementation engagement. This is an operating rule of EPISTEME, not a suggestion.
* All timelines are estimates. Actual duration is adjusted to each client's organizational context, complexity and pace of decision-making.
Do you know your organization's actual data maturity level? Before any transformation project — governance, analytics, AI — the answer to that question determines everything: the right framework, the right entry tier, the right sequencing. EP-00 is where every EPISTEME engagement begins.
Assess the organization's data maturity across all critical dimensions — strategy, governance, architecture, analytics, AI readiness and operations — using DAMA-DMBOK or the Data Governance Institute framework, selected and adapted to the organizational context. Delivers a prioritized transformation roadmap and a concrete recommendation on which service lines and tiers to activate.
00 — Service architecture
Each client enters where their maturity allows — always after the diagnosis confirms the starting point.
| Service line | EP-00 · Diagnosis | EP-01 · Essential | EP-02 · Complete | EP-03 · Strategic |
|---|---|---|---|---|
| 01 · Data Foundation | EP-DF-00Data Maturity Diagnosis | EP-DF-01Essential Governance | EP-DF-02Complete Governance | EP-DF-03Strategic Advisory |
| 02 · Analytics & BI | EP-AB-00Analytics Diagnosis | EP-AB-01Essential Analytics | EP-AB-02Complete Analytics | On request |
| 03 · Advanced Analytics | EP-AA-00Advanced Analytics Diagnosis | EP-AA-01Proof of Concept | EP-AA-02Complete Implementation | On request |
| 04 · AI Solutions | EP-AI-00AI Readiness Diagnosis | EP-AI-01AI Proof of Concept | EP-AI-02Complete AI Solutions | EP-AI-03AI Strategic Advisory |
Data governance, platform architecture, quality and compliance. Without this layer well-built, any investment in analytics or AI is fragile.
Assess the organization's current state across five data maturity dimensions and deliver a prioritized roadmap with concrete, actionable recommendations.
Implement a minimum viable data governance framework — ownership, basic quality and usage policies — establishing order and data reliability across the organization.
Design and implement a comprehensive data governance framework (DAMA-DMBOK) with data architecture, advanced quality, FinOps and compliance — covering all critical domains of the organization.
Provide ongoing strategic advisory in data governance — periodic reviews, framework evolution, architecture decision support and accompaniment of the internal team.
Reliable data turned into visible decisions. Executive dashboards, business KPIs, self-service analytics and automated reports — from C-level to operational teams.
Assess the organization's current analytics and BI capabilities — tools, processes, culture and adoption — and deliver an analytical maturity roadmap.
Implement an initial set of executive dashboards and business KPIs that convert existing data into operational visibility for leadership and key teams.
Implement a complete analytics platform with self-service, automated reports, Generative BI and data culture — enabling the entire organization to make data-driven decisions.
From describing the past to anticipating the future. Predictive models, forecasting, segmentation and anomaly detection. Designed for organizations that already have reliable data and want to extract maximum value.
Assess the organization's readiness for advanced analytics and predictive models — data quality, technical capabilities, priority use cases and ROI potential.
Develop and validate an advanced analytics model for a specific use case — demonstrating technical feasibility, business value and scalability path before full investment.
Develop, implement and deploy advanced analytics models into production — with basic MLOps, performance monitoring and organizational adoption — generating measurable, sustainable business value.
Applied AI for real problems. Not generic chatbots. Autonomous agents, applied LLMs, intelligent automation and custom AI — with governance built in from design and clear ROI metrics from day one.
Assess the organization's real readiness to adopt AI solutions — data, infrastructure, capabilities, governance and culture — and identify AI use cases with measurable ROI and manageable risk.
Develop and validate an AI solution applied to a specific client process — demonstrating feasibility, measurable business value and scalability path before full investment.
Design, develop and deploy AI solutions into production — with integrated governance, continuous monitoring and capability transfer to the internal team — generating measurable, sustainable business value.
Provide ongoing strategic advisory in AI and data governance for organizations in transformation — accompanying adoption decisions, scalability and AI governance on a recurring basis.
05 — Operating principles
EP-00 Diagnosis is mandatory before any EP-01, EP-02 or EP-03 — no exceptions.
Packages have fixed scope. Changes during the project are subject to formal change control.
The client is always responsible for operating their own systems — EPISTEME designs, configures and accompanies, does not operate.
All services include documentation as a deliverable — the knowledge stays in the client's organization.
Ethics and compliance are part of the design, not an add-on at the end.
Data democracy does not mean lowering quality. It means building the right foundations so organizations of all sizes access the same rigor previously reserved for large enterprises.
Every engagement starts with a conversation. Tell us where you are — we'll tell you honestly where to go.
Schedule a diagnosis →