Clear, owned outputs.
- Solution architecture
- A working prototype
- Production application or service
- Evaluation report
- Monitoring and maintenance plan
Off-the-shelf AI tools don't always fit your data, workflows or requirements. Custom AI development builds solutions around your specific problem: the right model or combination of models, your data, the systems people already use and the controls your organization needs.
The problems Custom AI Development solves.
Bespoke AI applications, models and integrations from prototype to production.
Generic AI tools don't understand your domain or data.
Data can't leave your environment for privacy or contractual reasons.
AI needs to plug into existing systems and workflows.
Prototypes work in demos but not under real conditions.
What Custom AI Development covers.
Solution design
Choosing models, architecture and integration points.
Model development
Classical ML, deep learning or LLM-based approaches as appropriate.
Application development
User interfaces and APIs around AI capabilities.
System integration
Connecting AI to CRM, ERP, document stores and other systems.
Evaluation
Test sets and metrics that reflect real-world use.
Deployment and MLOps
Secure deployment, monitoring and update processes.
From prototype to a system people rely on.
A demo and a production system are different things. We plan for the second from the start.
- 01
Define success
The metric the system is judged on and the threshold it must reach, agreed before any model is chosen.
- 02
Prototype
The simplest approach that could work, tested on real data within weeks.
- 03
Evaluate
A held-out test set and human review of failure cases, not just an average accuracy figure.
- 04
Integrate
APIs, user interface and the human review step built into the existing workflow.
- 05
Operate
Monitoring for drift and errors, a retraining or update process and a named owner.
Why it's worth it.
Fit for purpose
Built around your data and workflow.
Control
Deployment options that respect your security requirements.
Measurable value
Evaluation shows whether the system meets its goals.
When Custom AI Development is the right move.
- An internal tool that drafts responses using company knowledge.
- A model that classifies incoming requests and routes them.
- AI features added to an existing product.
Technologies & platforms
- Python
- PyTorch
- scikit-learn
- LangChain
- FastAPI
- Docker
- Kubernetes
- Azure OpenAI
- AWS Bedrock
- Vertex AI
How Custom AI Development work runs.
- 01
Frame
The decision or task to improve, the measure of success and the constraints.
- 02
Assess data
Availability, quality, access, privacy and labelling needs.
- 03
Prototype
A small, honest test of whether the approach can work.
- 04
Build and evaluate
Model development with documented evaluation against agreed criteria.
- 05
Deploy and monitor
Integration, monitoring for drift and performance, and retraining plans.
Custom AI Development questions.
Do you build from scratch or use existing models?
Usually we build on existing foundation models or proven libraries and customize them. Training from scratch is rarely necessary.
Can the solution run in our own cloud?
Yes. We can deploy within your cloud account or private network and use model providers that meet your data requirements.
Who owns the code and models?
Ownership is set out in the contract. Typically you own the custom code and any models trained on your data.
Talk to us about custom ai development.
Tell us which decision or process you want to improve and what data you have. We'll reply with whether it's a good fit and how we would test it.