Methodology
How We Build
Our approach combines cutting-edge agentic AI, rigorous behavioural science, and a partnership model that ensures we succeed only when you do.
The Three Pillars
Agentic Technical Mastery
We build enterprise-grade AI agents using MCP and UTCP protocols — modular, composable systems that can reason, act, and learn autonomously. These are not chatbots. These are intelligent systems that handle complex workflows end-to-end with appropriate human oversight.
Behavioural Science Integration
Every system we design accounts for human cognition — how people actually think, decide, and act. This is not UX design. This is deep behavioural modelling that ensures AI systems achieve real adoption and sustainable outcomes.
Partnership Methodology
We don't deliver projects and walk away. We embed with your team, co-own the outcome, and iterate until commercial impact is proven. Our incentives are aligned with yours — we succeed when the venture succeeds.
Process
The Engagement Model
Discovery & Behavioural Analysis
We immerse in your context — your industry, your users, your constraints. Our behavioural science team maps how decisions are actually made, not how they are assumed to be made.
Solution Co-Design
We architect the system together. Your domain knowledge combined with our technical and behavioural expertise. No black boxes — full transparency on trade-offs and decisions.
Build & Train
Our engineering team builds production-grade systems using enterprise agent creation, MCP/UTCP protocols, and modular agent chains. Every system is tested against real behavioural patterns.
Deploy & Integrate
We deploy into your existing infrastructure — not alongside it. Full integration with your systems, your workflows, your team. We don't leave until adoption is proven.
Continuous Optimisation
AI systems improve with data and feedback. We stay engaged post-launch — monitoring, refining, and evolving the system as your business and users evolve.
Capabilities
Technology Stack
Enterprise Agent Creation
- MCP & UTCP protocol implementation
- Modular agent chains for complex workflows
- Autonomous task execution with human oversight
- Multi-agent orchestration systems
Precision Matching
- Semantic matching across multiple parameters
- Behavioural nudge integration
- Real-time scoring and ranking
- Continuous learning from outcome data
Agentic-First UX
- AI-native interface patterns
- Human-AI collaboration workflows
- Adaptive experience layers
- Behavioural science-informed design
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