AI Solutions We Develop
AI Assistants & Conversational AI
Delivering Intelligent, Always-On Customer Support at Scale
Transform customer interactions with AI assistants that understand context, provide accurate responses, and scale your expertise across thousands of users simultaneously.
What We Build
- Intelligent chatbots powered by large language models
- Context-aware conversational AI that maintains dialogue flow
- Natural language understanding systems with safety boundaries
- Personalised response systems that adapt to user needs
Problems It Solves
- Providing 24/7 support and guidance to customers or users
- Scaling expert knowledge across large user bases
- Delivering personalised advice based on user context
- Reducing operational costs whilst improving user experience
Real-World Example & Impact
Example: A consumer app needed to evolve their AI chatbot architecture to support more rapid feature development. We conducted a comprehensive review and rebuilt the system with a cleaner, more maintainable architecture that better supported the team’s development workflow.
Impact: Response times improved dramatically, system reliability increased, and the development team could now ship new features quickly - accelerating the product roadmap and enabling faster iteration on user feedback.
Intelligent Document Processing & Classification
Automating Document Analysis to Unlock Insights from Unstructured Data
Stop manually processing thousands of documents. Let AI automatically extract, classify, and structure information at scale with consistent accuracy.
What We Build
- Automated document reading and classification systems
- Information extraction engines for unstructured text
- Batch processing systems that handle thousands of documents
- Entity and concept identification systems
Problems It Solves
- Eliminating manual analysis of large document collections
- Extracting structured information from unstructured text
- Processing hundreds or thousands of documents consistently
- Identifying key concepts, entities, and themes automatically
Real-World Example & Impact
Example: An education platform needed to process entire books to identify literary concepts and extract key information - work that would take teachers hours per book. We developed a batch processing system that could analyse books at scale, automatically extracting structured information and generating contextual vocabulary definitions.
Impact: Students can now use the online platform to quickly access the background knowledge and contextual information they need to understand the books they’re reading. The automated analysis provides immediate learning support at scale, helping students engage more deeply with complex texts in ways that would have been impossible to deliver manually.
AI Agents & Multi-Agent Systems
Building Intelligent Systems That Reason, Act, and Collaborate Safely
Deploy sophisticated AI systems that can handle complex, multi-step tasks autonomously whilst maintaining strict safety boundaries and appropriate behaviour.
What We Build
- Multi-agent systems with specialised capabilities
- Reasoning engines that break down complex problems
- Safety guardrail systems to prevent misuse
- Adaptive AI that responds appropriately to different scenarios
Problems It Solves
- Automating complex workflows that require multiple steps and decisions
- Providing intelligent assistance that can adapt to different scenarios
- Ensuring AI systems stay within safe and appropriate boundaries
- Scaling expert decision-making across large numbers of cases
Real-World Example & Impact
Example: Students needed immediate, personalised feedback on their work to support their learning - something that would be impossible to deliver manually at scale. We built an AI system that could provide constructive feedback whilst ensuring all interactions remained appropriate and safe for a learning environment.
Impact: Students now receive immediate feedback that supports their learning progress. The comprehensive safety measures ensure the system maintains appropriate educational standards at scale.
Intelligent Search & Knowledge Retrieval
Making Organisational Knowledge Findable and Actionable
Move beyond keyword search to semantic understanding. Help users find exactly what they need, even when they don’t know the right terms to search for.
What We Build
- Semantic search systems that understand query meaning
- Cross-document retrieval across large knowledge bases
- Context-aware search that provides grounded answers
- AI assistants powered by your specific content
Problems It Solves
- Finding relevant information in large, unstructured document collections
- Reducing time spent searching for information
- Enabling AI assistants to provide accurate, source-grounded answers
- Making organisational knowledge accessible and actionable
Real-World Example & Impact
Example: Policymakers needed to find relevant climate legislation across thousands of policy documents from around the world. Traditional keyword search wasn’t effective because similar policies were often described using different terminology. We built a semantic search system that could understand the meaning and intent behind queries, finding relevant policies even when they used completely different wording.
Impact: We architected and delivered a working MVP in just 8 weeks for COP 26, demonstrating how semantic search could help policymakers discover relevant climate legislation from across the globe. The rapid delivery proved the concept at a critical moment for global climate action, enabling the organisation to showcase the technology at the climate conference.
Predictive Analytics & Custom Machine Learning
Detecting Patterns and Predicting Outcomes That Humans Miss
Leverage custom machine learning to identify risks, predict behaviour, and make better decisions - from security threats to customer patterns.
What We Build
- Custom ML models tailored to your specific business problem
- Anomaly and threat detection systems
- Predictive models for customer behaviour and business outcomes
- Few-shot learning and fine-tuned models for specialised tasks
Problems It Solves
- Detecting patterns and anomalies that humans miss
- Making accurate predictions at scale
- Identifying high-risk situations before they become problems
- Improving decision-making with data-driven insights
Real-World Example & Impact
Example: A security company needed to detect sophisticated impersonation attacks where criminals were pretending to be senior executives. These attacks were hard to spot because they were carefully crafted to look legitimate. We developed a machine learning model that could identify these impersonations with high accuracy, even when processing millions of messages daily.
Impact: The solution addressed a critical client concern and became a key differentiator in sales. The system now protects thousands of organisations across multiple markets.
Optimisation & Decision Intelligence
Finding the Best Solution from Millions of Possibilities
Let AI evaluate options that would take humans years to consider, identifying improvements and optimisations that maximise your business objectives.
What We Build
- Optimisation algorithms for complex decision problems
- Resource allocation and scheduling systems
- Layout and configuration optimisers
- Multi-objective optimisation with practical constraints
Problems It Solves
- Making better decisions when there are too many options to evaluate manually
- Finding improvements that aren’t obvious to human experts
- Balancing multiple competing objectives and constraints
- Identifying small changes that deliver significant value
Real-World Example & Impact
Example: A retail space planning company needed to help their clients optimise store layouts to improve profitability, but couldn’t identify which changes would deliver the most value without extensive manual analysis. We developed an optimisation algorithm that could analyse patterns across multiple stores to identify profitable layout improvements, whilst respecting the practical constraints of each location.
Impact: We delivered a web-based interface showcasing the optimisation algorithm, along with a comprehensive business case with cost-benefit analysis. The solution provided a data-driven approach to identifying targeted, implementable improvements rather than requiring wholesale store reorganisations.