← All case studies Case study · Customer service
Customer-service organisation (consulting engagement) Delivered
Organisation Customer-service organisation (consulting engagement)
Industry Customer service
Region Not disclosed
Service area Conversational Agents
Problem type Accurate self-service answers
Used by Customers The challenge Customers needed accurate answers drawn only from the company’s own content — not generic answers from the open web.
What we built A retrieval-augmented generation (RAG) framework using a vector database and OpenAI GPT-4 that answers only from a curated set of uploaded content.
The outcome Customers get answers grounded in internal data only.
AI approach RAG Answers restricted to approved content
Tech stack OpenAI GPT-4 Vector database
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Book my free review Healthcare · Longevity & Traditional Chinese Medicine Pilot delivered
Longevity-health startup · China
Problem type Scaling scarce expert knowledge
Service area Conversational Agents
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 sources LLM fine-tuning Speech-to-text & text-to-speech Lip-synced video avatar
Tech stack Azure OpenAI GPT-4 Vector database Wav2Lip FastAPI
Read the case study → Healthcare · Mental health Delivered
Mental-health startup · UK
Problem type Round-the-clock patient support
Service area Conversational Agents
Used by Psychotherapy patients between sessions
The challenge Psychotherapy patients needed empathetic support between sessions, at any hour, when their therapist is not available.
What we built The open-source Falcon LLM fine-tuned on psychotherapist conversations to create an empathetic chatbot companion. Psychotherapists can support patients 24/7 with an empathetic AI companion.
AI approach Open-source LLM fine-tuning Empathetic dialogue design
Tech stack Falcon (open-source LLM)
Read the case study → Finance · Crypto Delivered
Crypto-finance startup · India
Problem type Up-to-date domain guidance
Service area Conversational Agents
Used by Viewers and retail crypto users
The challenge Viewers wanted to understand crypto, with answers and suggestions that keep pace with a fast-moving market.
What we built A chatbot trained on web data and crypto domain knowledge that gives users insights and suggestions in plain language. AI approach LLM chatbot Web data ingestion
Tech stack LLM Web data pipeline
Read the case study → Less manual work. More business.
Chennai, Tamil Nadu, India
MSME ID UDYAM-TN-02-0220640
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