Specialised Resource Injection

Your roadmap is ready. Your team needs reinforcement.

AI and data specialists embedded directly into your team - same stand-ups, same tools, same goals.

Request engineer availability

Tell us about the gap in your team - we'll let you know if we can fill it

Production-proven engineers

Deployed in weeks, not months

Your team, your IP

Your roadmap is ready. But you can't hire fast enough to execute it.

The talent market for senior AI engineers is brutal. While you wait, your competitors ship.

Senior ML engineers take 6+ months to recruit - if you can find them at all

Every month without the right people is a month your roadmap sits on a shelf. Competing offers, counter-offers, and notice periods turn hiring into a marathon.

Your data scientists are spending 80% of their time on data plumbing

You hired them to build models. Instead they are writing ETL scripts, cleaning datasets, and debugging pipeline failures. The modelling work that drives value keeps getting pushed back.

Offshore teams don't understand your compliance requirements

Financial services and telco have regulatory complexity that generic engineering teams struggle with. You need people who understand your data, your regulators, and your legacy systems.

If you don't have a clear AI roadmap yet, this isn't where you start. Our AI Roadmap gives you the plan first - so you know exactly what to build and what skills you need.

AI specialists working alongside your team

Why X-idian

We don't recruit. We deploy production engineers.

Your plan is clear

You have a prioritised AI roadmap and know what to build first.

Your leadership is in place

Internal technical leads own the architecture and delivery decisions.

Your infrastructure is ready

Cloud environments, data pipelines, and security frameworks are established.

You just need capacity

The bottleneck isn't direction - it's specialist hands on keyboards.

Model

Direct integration, not outsourcing

Our engineers become part of your team from day one. Same tools, same stand-ups, same goals.

Our engineers join your daily stand-ups, use your tools, and report to your technical leads
You own the roadmap, the architecture, and the outcomes
We provide the specialist skills your team is missing to accelerate delivery
No management overhead from our side. No separate workstream. No status reports to two bosses

Roles

Roles we typically embed

Specialists with production AI experience across the full delivery lifecycle.

Machine Learning Engineers

Models built for your infrastructure and deployed into your production environment.

Data Engineers

Reliable pipelines that keep your AI systems fed with clean, trusted data.

Data Scientists

Analytical models that turn complex data into decisions your team can act on.

Generative AI / LLM Engineers

Large language models fine-tuned for your specific business context and data.

NLP / Conversational AI Engineers

Conversational AI and document intelligence that understands your customers and your domain.

Computer Vision Engineers

Visual recognition and inspection systems that automate what human eyes can't scale.

MLOps / Platform Engineers

Your models stay accurate, monitored, and running reliably after deployment.

AI Solutions Architects

Technical leadership that ensures your AI programme integrates cleanly with existing systems.

Data Analysts

Dashboards and insights that help your team measure what your AI is actually delivering.

The Difference

Production engineers, not recruiters.

We vet for engineers who have built and deployed AI in production - not just trained models in notebooks. Where possible, we match for industry experience so they understand your data, your compliance requirements, and your legacy systems.

vs staffing agencies

We vet for delivery capability, not keyword matches. Every engineer has deployed AI in production.

vs offshore teams

Same timezone, senior-level, production-proven. No communication overhead.

vs permanent hiring

Deployed in weeks, not months. No recruitment fees, no onboarding lag.

Weeks

To deploy

Production-proven

Every engineer