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Applied AI · Senior UK developer
AI systems your team can actually use
Practical AI adoption for businesses: custom skills, useful knowledge systems, documented workflows and team support without the vague transformation theatre.
The outcome
What good looks like.
A secure, explainable AI setup built around real business work—with the team trained, the source material organised and human responsibility kept visible.
- 01Routine enquiries and admin handled faster
- 02Support teams spend more time on exceptions
- 03Consistent outputs grounded in business knowledge
- 04Documented ownership, escalation and privacy controls
Included
A practical scope, shaped around the job.
AI live chat and helpdesk assistance
MCP servers and custom system connections
Team onboarding, governance and improvement
Start with useful work, not an AI shopping list
Give the team leverage without giving up judgement.
The best first use is usually narrow, frequent and measurable: finding trusted information, drafting from approved source material, turning a repeated process into a skill, or helping a team manage work consistently.
Custom agents and internal copilots
Build role-specific helpers that can follow a process, use approved knowledge and hand work back to a person.
- Business-specific agents
- Custom skills and tool access
- Structured output and actions
- Human approval and escalation
Live chat and helpdesk AI
Help customers get useful answers sooner while keeping the support team in control of sensitive or unusual cases.
- Website and in-product chat
- Helpdesk classification and routing
- Suggested replies and summaries
- Knowledge-grounded self-service
Connected workflows and MCP servers
Let approved agents work across the systems the business already uses through existing or custom MCP tools.
- Inbox and request triage
- CRM and helpdesk actions
- Existing and custom MCP servers
- Reports, hand-offs and reminders
How the work joins up
Adoption is a people-and-information project as much as a technical one.
I can work with leadership, operations, marketing and technical teams to define useful boundaries, create shared working methods and make sure responsibility never disappears into the model.
Discuss the right approachOpportunity mapping
Find the annoying work worth removing.
Score repeated tasks by volume, value, risk, available knowledge and the need for judgement.
Knowledge and documentation
Give agents reliable source material.
Organise policies, FAQs, procedures, examples and terminology so answers are grounded in the business.
Team and customer experience
Design the hand-off, not just the happy path.
Define when AI responds, when it drafts, when it asks and when a named person takes over.
Management
Keep the system owned and current.
Define access, change control, feedback, measurement and who remains accountable.
Built into the service
Useful AI needs boundaries, evidence and someone responsible.
Business data and access handled according to an agreed risk model.
Outputs tied to approved documents, examples and sources where possible.
Decisions and sensitive outputs retain named human ownership.
Skills tested against representative tasks before wider adoption.
Instructions, dependencies and limitations stay visible.
Usage and feedback inform controlled changes rather than prompt drift.
MCP and connected systems
Give AI approved tools, not unrestricted access.
I can provision the infrastructure and connect agents to the systems they need through existing MCP servers or a purpose-built MCP when the required tool does not exist.
Helpdesk, CRM, databases, documents, email, project tools and internal APIs.
Documented tools, typed inputs, authentication, permissions and controlled actions.
Custom agents and skills that can find information or take approved actions.
Deploy the connection properly.
Runtime, domains, authentication, secrets, environments and deployment pipelines configured for the service.
Expose only the tools the workflow needs.
Purpose-built tool definitions and resources over an existing API, database or internal system.
Know what the agent can do.
Scoped permissions, validation, logs, rate limits, approvals, monitoring and a clear human escalation route.
Keep the integration dependable.
Versioning, documentation, incident diagnosis and maintenance as the connected systems change.
Where AI can take the load
Start with the work everyone is tired of doing.
The goal is not to remove people from the business. It is to stop skilled people spending their day searching, copying, categorising and writing the same first response.
Give every enquiry a useful first step.
- AI live chat grounded in approved FAQs and policies
- Helpdesk ticket classification, priority and routing
- Reply suggestions, conversation summaries and next actions
- Clear escalation for complaints, risk and uncertainty
Move information without the copy-and-paste shift.
- Shared-inbox and request triage
- Extract data from forms, PDFs and email attachments
- Update CRM, helpdesk and project records
- Create hand-offs, reminders and exception queues
Stop asking where the answer lives.
- Internal assistants over policies and documentation
- Role-specific skills for repeatable team tasks
- Meeting, case and project summaries
- Draft procedures and documentation from approved work
Prepare the work before a person makes the decision.
- Lead research and qualification support
- Proposal and account-summary preparation
- Content repurposing with brand controls
- Weekly reporting and anomaly summaries
How the work moves
Clear stages. Visible progress.
- 01
Find the repetitive work creating the most drag
- 02
Map the knowledge, systems and human hand-offs
- 03
Build and test agents, assistants and workflows
- 04
Train the team, measure the load removed and improve
Applied AI · Common questions
Useful answers before we speak.
Specific answers about this service, its scope and the decisions that usually matter before work begins.
What business work can AI help with?
Good candidates include repetitive support questions, live-chat triage, helpdesk drafting, inbox and document classification, internal knowledge search, meeting preparation and routine administration.
What is a custom AI agent?
A custom agent follows defined instructions, uses approved knowledge and tools, completes a limited workflow and hands work to a person when judgement or authority is required.
Can AI connect to our helpdesk, CRM and documents?
Yes. Existing APIs, approved integrations, MCP servers or custom MCP tools can connect an agent to the systems it needs, with deliberately limited permissions.
Can AI help with live chat without replacing the team?
Yes. It can answer routine questions, gather context, classify requests and draft responses, while clear escalation rules keep sensitive, unusual or high-value conversations with people.
How do you protect private business and customer data?
The design begins with the data, risk and access model. Provider choices, least-privilege permissions, logging, human review and retention controls are agreed for the specific workflow.
How should we start using AI in the business?
Start with one frequent, low-risk and measurable source of drag. Map the knowledge and human hand-offs, build a controlled pilot, test it with real cases, train the team and measure the load removed.
Complementary expertise
This rarely lives in isolation.
Most useful systems cross more than one discipline. Add the expertise that makes this service easier to launch, operate and improve.
01WebsitesWebsite development that earns its keep
A website appropriate to the business—not a needlessly complicated build—with the option to bring in trusted copywriting and brand specialists when the work needs them.
↗02Custom productsCustom software that gets out of the sketchbookOne accountable technical partner across product thinking, architecture, development, deployment and the decisions between them.
↗03InfrastructureHosting and infrastructure without the finger-pointingA calmer, documented technical foundation with one person responsible for understanding how the pieces fit together.
↗04Maintenance and partnershipTechnical support that already knows the systemProactive care, clear priorities and direct access to the senior developer doing the work.
↗A useful first step
Bring the messy version.
I’ll help make it clear.
You do not need a polished specification before we speak. A short conversation is enough to identify the sensible next move.