Overview
What You Can Expect (Tailored to your Priorities)
A structured, cross-functional engagement tailored to your industry, maturity, and strategic priorities. This includes:
A tailored AI transformation roadmap
Prioritized use case portfolio with business cases
Governance and risk frameworks
Custom model development and delivery architecture design
Cultural and organizational enablement plan
Modular Engagement Structure
- Strategy Definition
Align AI and GenAI initiatives with enterprise objectives
Assess organizational maturity and AI readiness
Identify and prioritize high-value, feasible use cases
Design scalable governance and operating models
- Program & Portfolio Management
Stand-up and operate a dedicated AI PMO
Coordinate stakeholders across business and tech functions
Track value realization and support agile iteration cycles
- Model Development & Deployment
Evaluate use case feasibility (technical + algorithmic)
Design, build, and validate custom AI/ML models
Implement scalable delivery pipelines with monitoring and retraining
- Data & Analytics Readiness
Assess data architecture and governance maturity
Design scalable data pipelines to support model performance
Provide build vs. buy support for key AI platform decisions
- Secure AI Architecture
Conduct security reviews and penetration testing
Embed controls at key integration points (e.g. APIs, data access)
Ensure secure deployment environments across cloud and hybrid stacks
- Responsible AI & Compliance
Define ethical principles and regulatory policies
Evaluate and document risks for sensitive use cases
Establish model traceability, explainability, and audit mechanisms
- Change Management & Upskilling
Design tailored training programs for technical and business teams
Support adoption across business lines and functions
Align workforce culture with new AI operating models
Optional Add-On: SiaGPT
SiaGPT, our proprietary GPT-based assistant, can be delivered alongside this engagement. Offered in white-label mode and fully customizable, it enables clients to deploy secure, use-case-specific generative AI applications quickly and safely.
Timeline & Delivery Format
Engagement Length: Typically 4–8 weeks, depending on scope
Delivery: Remote or hybrid workshops, stakeholder interviews, and technical deep dives led by our multidisciplinary team.
We are working on various AWS infrastructures (Bedrock, Q, SageMaker...) and our products rely on differents AWS services when creating and deploying a platform or a software for a customer.
Highlights
- End-to-end capabilities spanning strategy, delivery, risk, and enablement.
- Domain depth across financial services, life sciences, energy, consumer, technology, and more.
- Proven accelerators that reduce time-to-impact for GenAI and ML programs. Integrated teams across Business Ă— Data & AI Ă— Cybersecurity Ă— Compliance.
Details
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Pricing
Custom pricing options
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