AI Development Services
Custom AI development, from prototype to production
Our engineers build AI that works reliably in the real world: agents, LLM applications, document AI, machine learning models and more. We handle the full lifecycle, from design and data to deployment, monitoring and security.
Who our AI development services are for
- CTOs and engineering leaders adding AI to products or internal platforms
- Product teams that need an AI feature built and shipped fast
- Operations leaders with a specific automation or prediction problem
- Companies whose AI prototype works in a demo but not yet in production
Problems AI development solves
AI development capabilities
Agentic AI Development
- Custom AI agents and multi-agent systems
- chatbots and assistants for websites, Microsoft Teams, Slack and WhatsApp
- Model Context Protocol (MCP) servers and agent tools
- voice AI agents for inbound and outbound calls
- Looking for a ready-made business solution? See AI agents for business →
AI Automation & Integration
- AI workflow and process automation
- AI integration with apps, APIs, ERP/CRM systems and databases
- AI features for web and mobile apps
- For AI inside your existing ERP or CRM, see AI for ERP & CRM →
LLM & Generative AI
- Custom LLM applications
- RAG and AI-powered search
- LLM fine-tuning
- prompt engineering and LLM evaluation
- For a ready-to-deploy company knowledge assistant, see private RAG copilots →
Document AI
- OCR and intelligent document processing
- data extraction from invoices, forms, contracts and claims
- For invoice, bill of lading and claims automation, see intelligent document processing →
Machine Learning & Predictive AI
- Custom ML models
- forecasting, churn and recommendation models
- fraud and anomaly detection
Computer Vision, Speech & Language AI
- Image and video analytics and object detection
- speech-to-text and text-to-speech
- text classification, summarization and machine translation
MLOps & AI Security
- Model deployment to cloud, private cloud or on-premises, with monitoring
- GPU and cloud infrastructure setup and cost optimization
- AI guardrails, red-teaming and security testing
How our AI development process works
Discover.
We clarify the goal, users, data, constraints and how success will be measured.
Design.
We choose the architecture, models and integration approach, and agree the scope.
Prototype.
We build a working proof of concept on your data and evaluate it against agreed metrics.
Engineer for production.
We add security, testing, monitoring, scaling and integration with your systems.
Deploy and support.
We launch in your environment, hand over documentation, and offer ongoing support and improvement.
AI development use cases
Example scenarios, not client projects.
Home services company: voice AI agent.
An AI voice agent answers after-hours calls, books appointments into the scheduling system and sends urgent jobs to the on-call technician.
Online retailer: churn and recommendations.
ML models predict which customers are likely to leave and recommend relevant products, feeding personalized email campaigns.
Manufacturer: visual quality inspection.
A computer vision model checks products on the line for defects from camera images and flags faulty items for removal.
AI development tech stack
- Languages and frameworks
- Python, TypeScript, PyTorch, scikit-learn, LangGraph, Hugging Face
- AI models
- leading commercial LLMs, plus open-source models hosted privately
- Data and retrieval
- PostgreSQL, vector databases, data warehouses and lakehouses
- Cloud and MLOps
- AWS, Microsoft Azure, Google Cloud, Docker, Kubernetes, CI/CD and model monitoring
- Security
- guardrails, red-team testing, secrets management and role-based access
AI development engagement models
Build
A dedicated delivery team builds and ships your AI solution end to end.
Consult
Senior engineers review your design, choose models and plan the build with your team.
Staff
AI and ML engineers join your team to build alongside your developers.
AI development services FAQs
Which AI models do you use?
Whichever fits your needs best. We work with leading commercial models and open-source models, and choose based on accuracy, cost, speed and data privacy.
Can you deploy AI in our own environment?
Yes. We deploy to your cloud account, a private cloud or on-premises servers, including GPU infrastructure.
Who owns the code and models?
You do. On delivery, you own the code, configurations and trained models built for you, as set out in the contract.
How do you test AI quality?
We build evaluation sets from your real cases and track accuracy, safety and cost before and after launch.
Can you take over or fix an existing AI project?
Yes. We start with a technical audit, then stabilize, improve or rebuild as needed.
Need people rather than a project?
Hire AI engineers →Need training data?
AI data and annotation services →Not sure where to start?
AI readiness assessment →
What happens next
Book a call.
A free 30-minute technical consult about your use case.
Free assessment.
We review your requirements, data and systems and recommend an approach.
Proposal.
A clear scope, timeline and price, often starting with a proof of concept.
Have an AI project in mind?
Tell us what you want to build. We'll help you choose the right approach and give you a realistic plan to get it into production.