Fast onboarding
Flexible engagement
Production-ready code
Challenges You Can Solve with Easyflow
Remove the obstacles that slow AI projects.
Hiring Delays
Recruiting skilled AI engineers takes months, slowing your projects.
Cost of Talent
Hiring elite AI talent can often be pricier than entire dev teams.
Slow Adoption
Resistance to change and outdated practices stall AI initiatives.
Legacy Drag
Old code and processes make AI adoption slow and painful.
Product-Integrated LLMs
Add AI-powered search, recommendations, and smart assistants directly into your product.
Integrations & Automations
Link AI systems end-to-end with your business tools to automate workflows, sync data, and reduce manual work.
Code Migration & Refactor Engineering
Legacy code shouldn't be a barrier to innovation. Modernise codebases to support AI automation and new workflows.
Fine-Tuning & Model Adaptation
Adapt LLMs to your data, policies, and edge cases to improve accuracy, reduce hallucinations, and align with internal rules.
Data & ETL Orchestration
The foundation of AI is clean data. Prepare and manage clean data pipelines to fuel high-performing AI systems.
Our Engineering Approach
Step 1
Architecture Design
We plan how AI will work with your data and systems to maximise impact.
Data strategy
System integration
Scalability
Step 2
Model Orchestration
Model selection
Task coordination
Performance optimisation
Step 3
Workflow Integration
Tool connectivity
Process alignment
User adoption
Step 4
Testing & Monitoring
Output quality
Performance tracking
Continuous improvement
Flexible AI Engineering Teams
Choose the right engagement model for your AI project.
Why Easyflow?
Dedicated Experts
A focused team ensures consistent attention and fast execution.
Bi-Weekly Sprints
Every 14 days, we commit to specific deliverables you set as priorities.
Rapid Scoping
You submit a task and get a clear, actionable plan within 24 hours.
Consistent Delivery
We commit to story points per sprint, ensuring steady progress.