AI agents and apps that do real work.

Problem type

Personalisation at scale

Service area

Recommendation Systems

Used by

Travellers planning trips

The challenge

Travellers wanted destination suggestions that matched who they are — adventure, business, nature, family or couples — not a generic list. It also had to stay fast and affordable as usage grew.

What we built

An end-to-end AI pipeline: data prepared with AWS Glue and Spark, BERT classifiers that profile traveller personas, and multi-agent orchestration on AWS Bedrock combining graph and document retrieval so every suggestion is grounded in real data.

Personalised recommendations in production, with cost and latency cut at scale through prompt caching, model right-sizing and batch processing.

AI approach

Multi-agent orchestrationGraph + vector RAGPersona classificationPrompt caching & model right-sizing

Tech stack

AWS BedrockAWS GlueApache SparkBERT

Problem type

Fragmented multi-role workflow

Service area

Web Portals & Apps

Used by

Administrators, charity directors and donors

The challenge

Admins, charity directors and donors managed donor-advised fund accounts and grant decisions across separate tools, with no shared place to discuss, vote and decide.

What we built

A role-based portal with dedicated Admin, Charity Director and Donor views, built-in chat, an insights view, a voting workflow for funding decisions and AI-assisted lookups — integrated with the custodial platform that holds the fund accounts.

Live and running in production for all three user roles.

AI approach

Role-based accessVoting workflowLLM chat & AI lookupsCustodian platform integration

Tech stack

Web portalLLM chatThird-party API integration

Problem type

Customer & market insight

Service area

Insights Engine

Used by

Optometry equipment manufacturers

The challenge

Optometry equipment manufacturers wanted to understand how their products are received across different demographic groups — evidence sales figures alone could not give them.

What we built

A production chat and insights platform over an enriched knowledge base. Retrieval keeps every answer grounded in source data, and sentiment analysis rolls up into brand-sentiment reports and dashboards.

Manufacturers get grounded, demographic-level insight into how their products are accepted.

AI approach

RAG over an enriched knowledge baseSentiment analysisGrounded report generation

Tech stack

LLM chatVector retrievalInsight dashboards

Problem type

Manual document processing

Service area

Document & Content Automation

Used by

Legal staff preparing deed orders

The challenge

Preparing deed orders from title commitment documents was slow and manual, and every deed type needed a different template.

What we built

GPT-4 reads each uploaded title commitment and extracts the grantors, grantees, property address, state and county. A staff member confirms the details, then the correct deed template is filled automatically, emailed through a Make (Integromat) workflow and filed in Google Drive.

10× less manual effort on deed preparation, with 100% precision through human-in-the-loop validation.

AI approach

LLM document extractionHuman-in-the-loop validationTemplate-based generationWorkflow automation

Tech stack

OpenAI GPT-4Make (Integromat)Google Drive

Problem type

Scaling scarce expert knowledge

Service area

Conversational Agents

Used by

Patients

The challenge

The client wanted a visual expert that could talk with patients, help identify their issues and respond with empathy — answering strictly from approved Chinese medical texts, with no made-up advice.

What we built

Approved medical texts in a vector database with RAG on Azure OpenAI; GPT-4 fine-tuned for an empathetic, doctor-style manner; speech-to-text and text-to-speech for voice; and a Wav2Lip lip-synced video avatar served through a FastAPI web app.

Pilot delivered with 100% precision on generated answers and no hallucinations; validated for production development.

AI approach

RAG on approved sourcesLLM fine-tuningSpeech-to-text & text-to-speechLip-synced video avatar

Tech stack

Azure OpenAI GPT-4Vector databaseWav2LipFastAPI

Problem type

Manual prospecting & outreach

Service area

Document & Content Automation

Used by

Sales and marketing team

The challenge

Finding B2B leads and writing tailored outreach took hours of manual research per prospect, which capped how many targets the team could reach.

What we built

An engine that crawls market intelligence on target companies and generates targeted outreach content automatically, ready for the team to review and send.

B2B lead generation and marketing running at scale — designed and built from the ground up.

AI approach

Web crawlingMarket-intelligence extractionLLM content generation

Tech stack

Web crawlersLLM content generation