Agents
Handle routine requests
People answer the same questions and requests by hand.
Agents that prepare answers, gather information or carry out defined steps, with a person validating what matters.
AI integration and automation
AI in the toolsyour teams already use.
Agents, workflows, CRM, knowledge bases, internal assistants and connectors. We integrate AI where repetitive work happens: a pilot on one priority use first, then a rollout of what proves useful.
One priority use → pilot → rollout → ongoing support
01 / What we integrate
Start with the repetitive work.
Each integration begins with a task that someone actually does, repeatedly, today.
Workflows
Connect the steps
Work moves between tools by copy and paste, and steps get missed.
Automated workflows that pass information between your tools, with clear rules, logs and error handling.
CRM
Keep customer data useful
Contact records are incomplete, and follow-up depends on memory.
CRM integrations that capture, enrich and route information, so the next action is visible.
Knowledge bases
Make knowledge findable
The answers exist, but in documents that nobody can find.
Knowledge bases built from your own documents, with sources shown and an owner for each topic.
Internal assistants
Help teams where they work
New and busy team members interrupt colleagues to ask.
Internal assistants that answer from approved material, and say when they do not know.
Connectors
Join the systems
Systems do not talk to each other, so data is retyped.
Connectors between the tools you already run, rather than a replacement of them.
02 / From pilot to rollout
Pilot first. Roll out what works.
We begin with one priority use and extend only once it is validated. Scope, dependencies and acceptance criteria are agreed before delivery commitments.
- 01
Choose one use
Pick a single task with a clear owner, a clear volume and a way to tell whether it improved.
What makes the next step concrete: Use case and success criteria - 02
Design the pilot
Define the data, the tools, the human checkpoints and the limits. Decide what the system may do alone and what needs approval.
What makes the next step concrete: Pilot design and safeguards - 03
Build and connect
Build in reviewable increments and connect the tools involved. Handle failures, not only the happy path.
What makes the next step concrete: Working pilot and documentation - 04
Test with the team
Run the pilot with the people who will use it, on real cases. Compare the outcome with the criteria agreed at the start.
What makes the next step concrete: Measured pilot results - 05
Roll out
Extend what worked to the wider team: access, training, documentation and a named owner.
What makes the next step concrete: Deployment and handover - 06
Support and improve
Review use and results over time. Maintain, fix and improve, with changes prioritised against business needs.
What makes the next step concrete: Monthly support and evolving plan
03 / Control
People stay in charge.
AI is useful when it removes repetitive work and leaves judgement to people. These points are set out for each integration.
Human review where it matters
We define which actions are automatic and which need a person's approval, and keep a record of what the system did.
Sources and limits
Assistants answer from approved sources and are designed to say when they cannot answer, rather than guess.
Data and accounts
Define who owns the accounts, where data is processed and who may access it. Prefer accounts you control, and document how to export or leave.
Costs you can see
Development, licences, AI usage and support are shown separately, so running costs are never a surprise.
Practical questions
Do we have to replace our tools?
No. The aim is to connect what you already use. Replacement is a separate decision, taken only where it is justified.
Which AI models do you use?
The model is chosen per use case, based on the task, the data involved and your constraints. The choice and its dependencies are explained before the build.
How do you measure results?
Against criteria agreed before the pilot starts, such as time spent on a task, errors or response delays. We report what was measured, and say when something could not be measured.
Can we start without an audit?
Yes, if one workflow is already clear. When priorities are unclear, an AI audit is the better first step.
Other services
Start with one workflow
Which repetitive task should go first?
Describe the task, the tools involved and who does it today. That is enough to discuss a pilot.
Describe a workflowNo technical specification needed to start.