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AI Deployment & Strategy

Practical AI adoption — from readiness assessment to secure, governed deployment in production.

Starting from

$3,500

USD · scope-dependent

4–12 weeksDedicated senior consultantEN/FR delivery
Get a quote

Overview

AI is no longer a future technology — it is a competitive differentiator available today. We help organisations cut through the hype and implement AI that actually works: integrated with your existing systems, governed responsibly, and secured against emerging threats. From selecting the right LLM to building custom AI agents and complying with NIST AI RMF or the EU AI Act, we deliver end-to-end AI strategy and execution.

What we cover

Every engagement is tailored to your needs — pick one module or combine them.

AI Readiness Assessment

Evaluate your data quality, infrastructure, team capabilities, and business processes to build a realistic AI adoption roadmap.

LLM Integration & RAG Systems

Integrate GPT-4, Claude, Mistral, or open-source models into your products and workflows using retrieval-augmented generation and fine-tuning.

Process Automation with AI

Identify high-ROI automation opportunities and implement AI-powered workflows that eliminate repetitive tasks and accelerate decision-making.

Custom AI Agent Development

Design and deploy autonomous AI agents for customer support, document analysis, research, code review, or any domain-specific workflow.

AI Governance & Compliance

Build responsible AI frameworks aligned to NIST AI RMF, EU AI Act, and emerging regulations — policies, risk registers, and model cards included.

AI Security & Red-Teaming

Assess your AI systems against prompt injection, data poisoning, model inversion, and adversarial attacks — with a hardening remediation plan.

Included deliverables

AI readiness report & capability gap analysis
Strategic AI roadmap with prioritised use cases
Architecture design & model selection rationale
Proof-of-concept implementation or integration
AI governance framework & responsible use policy
Security assessment report with hardening plan
ROI model & total cost of ownership analysis
Team training & handover documentation

Our process

1

Discover & assess

We audit your data, systems, and processes to identify where AI creates the most business value and what barriers exist.

2

Strategy & architecture

We design the AI solution — model selection, data pipelines, integration points, governance framework, and security controls.

3

Pilot & validate

A focused proof-of-concept is built, tested with real data, and evaluated against defined KPIs before full deployment.

4

Deploy & govern

Full production deployment with monitoring, bias detection, model drift alerting, and a governance operating model your team can maintain.

Frequently asked questions

Do I need large volumes of data to benefit from AI?

Not necessarily. Many powerful AI use cases — document Q&A, customer support automation, summarisation — work well with existing business documents and data using RAG techniques. We assess your situation and recommend the right approach for your actual data reality.

Which AI models do you work with?

We are model-agnostic. We work with OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), Mistral, and open-source models like Llama. Model selection is driven by your use case, data sensitivity, cost constraints, and compliance requirements.

How do you handle data privacy when integrating LLMs?

Data privacy is embedded in our architecture from day one. We evaluate on-premise vs. cloud deployment options, implement data masking where needed, review vendor data retention policies, and ensure your AI deployment complies with applicable regulations (TDPSA, GDPR, HIPAA).

Start your project

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