AI Consulting Services
Identify high-ROI AI opportunities and build a practical roadmap from pilot to production.
Learn more →01 — AI & ML
AI, Machine Learning & Intelligent Automation
From strategy to production MLOps, we design, build and scale AI systems that automate work, sharpen decisions and create new AI-powered products — responsibly and securely.
- AI readiness & roadmap
- Proof of concept
- Model development
- Integration
- Years of delivery
- 8+
- Years of delivery
- Projects shipped
- 350+
- Projects shipped
- Clients across US, UK, AU & SG
- 200+
- Clients across US, UK, AU & SG
Our services
AI & ML services
Generative AI, agents and ML models that turn your data into a competitive edge.
Generative AI Development Services
Build GenAI products for content, code, search and workflows on leading foundation models.
Learn more →AI Agent Development Services
Autonomous agents that plan, use tools and complete multi-step business tasks reliably.
Learn more →Custom Machine Learning Development
Bespoke ML models trained on your data for prediction, classification and recommendation.
Learn more →Deep Learning Development Services
Neural network solutions for complex vision, speech, language and signal problems.
Learn more →NLP Development Services
Extract meaning from text with classification, entity extraction, summarisation and sentiment.
Learn more →Computer Vision Development Services
Image and video intelligence for detection, inspection, OCR and visual search.
Learn more →AI Chatbot Development Services
Conversational assistants for support, sales and internal help desks across every channel.
Learn more →LLM Fine-Tuning & RAG Development
Ground LLMs in your knowledge base with retrieval pipelines and domain fine-tuning.
Learn more →RPA Development Services
Software robots that automate repetitive, rules-based work across your systems.
Learn more →AI Integration Services
Embed AI capabilities into your existing products, CRMs, ERPs and workflows.
Learn more →MLOps Services
Deploy, monitor and retrain models with reliable, automated ML pipelines.
Learn more →Use cases
Solutions by industry
Healthcare
Clinical note summarisation and medical image triage.
Fintech
Fraud detection, KYC automation and credit scoring.
E-commerce
Personalised recommendations and AI shopping assistants.
Logistics
Demand forecasting and route optimisation.
Case studies
Featured work
Fintech lender
AI underwriting that approves loans in minutes
70
faster loan approvals
D2C retail brand
Headless storefront that survives peak season
140
online conversion
Technology
Tools & technologies
OpenAI
Anthropic Claude
Llama
LangChain
PyTorch
TensorFlow
Hugging Face
Pinecone
pgvector
MLflow
AWS SageMaker
Azure AI
Process
How we deliver
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01
STEP 01
Discover
Map use cases, data sources and success metrics.
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02
STEP 02
Prototype
Build and evaluate a PoC on real data.
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03
STEP 03
Productionise
Harden, integrate and secure the solution.
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04
STEP 04
Operate
Monitor, retrain and improve continuously.
“They rebuilt our platform in record time and the engineering quality is outstanding. It felt like an extension of our own team, not an agency.”
“Their AI team turned a vague idea into a production assistant that now handles most of our support queries.”
“Transparent, responsive and genuinely invested in our outcomes. Cloud costs dropped within the first quarter.”
“We had three developers onboarded in under two weeks, and they were productive from the first sprint.”
“The design work paid for itself. Checkout drop-off fell the week after launch and never went back up.”
“Security questionnaires used to stall our enterprise deals. They got us audit-ready in one quarter.”
FAQ
AI & ML FAQs
We start with a short discovery workshop that scores use cases by value, feasibility and data readiness, so you invest only where AI clearly pays off.
We are model-agnostic and work with OpenAI, Anthropic Claude, Google Gemini, Llama, Mistral and custom models, choosing based on accuracy, cost and data-privacy needs.
Yes. We use enterprise endpoints with no training on your data, private deployments where required, PII redaction and role-based access controls.
A proof of concept typically takes 3–4 weeks; a production-grade solution usually takes 8–16 weeks depending on integrations.
Yes. Our MLOps retainers cover monitoring, evaluation, model updates and cost optimisation.
Taking new projects
Ready to start your AI & ML project?
Tell us about your project and get a free consultation and estimate within 24 hours.
- We reply within 4 business hours A real consultant reads your brief — no bot, no queue.
- 30-minute discovery call We dig into goals, constraints and budget. NDA signed on request.
- Proposal in 24 hours Scope, timeline, team and price — clear enough to decide on.
NDA on request You own the IP No obligation Free estimate