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Solutions

AI Value-Driven Adoption for Reliability and Growth

Standard Bank
Pure Storage
John Hancock
Logex
Kalibrate
Amarr
Metropolitan Opera
Mercer
HBO
Nielsen

Why Transformation Can’t Wait

AI isn’t just an innovation driver—it’s a growth multiplier. But without structure, it can quickly create risk, inefficiency, or reputational damage.

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Unrealized ROI

Without clear governance, AI projects stall before reaching production, wasting investment and momentum.

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Compliance Pressure

Global regulations are evolving fast—turning responsible adoption into a business necessity.

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Model Drift & Bias

Unsupervised models lose accuracy and fairness over time, impacting performance and decision quality.

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Security and Privacy Risk

Weak control over data and model access increases exposure—and erodes customer trust.

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Ethical Accountability

Transparency builds confidence—for employees, customers, and regulators alike.

3%

of executives say governance is the biggest barrier to AI adoption.

(Source: Exadel AI Readiness Survey)

74%

of enterprises say governance improves AI ROI by enabling faster, safer scaling.

(Source: Exadel AI Readiness Survey)

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Our Framework

Driving Meaningful Progress at Scale

Exadel helps enterprises realize AI’s business potential—responsibly, measurably, and at speed.

01

Define

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Align Value, Risk, and Readiness

We assess your current data, processes, and AI maturity to identify high-value opportunities and the guardrails needed to support them. This creates a clear foundations document—linking business outcomes to global standards—so every AI investment starts with purpose, transparency, and feasibility.

02

Deploy

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Prove Impact with Anchored AI

We move pilots into production using Anchored AI—our governance accelerator that enforces traceability, auditability, and responsible controls. By validating performance early and embedding safeguards into every layer, teams build confidence in AI outputs while accelerating time-to-value.

03

Scale

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Govern Long-Term Performance and Growth

We embed continuous monitoring, model lifecycle management, and structured feedback loops to maintain accuracy, stability, and fairness at scale.
This ensures AI remains predictable and compliant as conditions change—protecting trust while unlocking new opportunities for automation and innovation across the enterprise.

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See how to scale AI without increasing risk or losing control.

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