Workflow automation
Connect email, forms, documents, CRM and ERP through available APIs and connectors. Include validation, duplicate protection, retries and a clear record of what happened.
Build / Less chasing. More progress.
AI agents & workflow automation.
Connect AI agents and automation to your existing business tools. We build workflows that gather information, prepare decisions and carry out agreed actions, with people in control of the important steps.
Discuss this with usThe opportunity
Let work move between your systems.
Information arrives in an inbox, gets copied to a spreadsheet and eventually reaches a CRM. People chase missing details and repeat the same checks. The process works, but it depends on constant attention.
We map the entire workflow before choosing the tools. Predictable steps use rules and integrations; AI helps with unstructured information and decisions that require context. Actions, permissions, approval points and failure behaviour are designed together.
What we can do.
Tool-using AI agents
Build agents that use approved tools to retrieve context, draft updates and complete bounded tasks. Define their permissions, stopping conditions and escalation rules.
Human review & orchestration
Route uncertain outputs and consequential actions to the right person. Make it possible to inspect the source, correct a draft, approve a change or recover from a failed step.
Tangible outputs
What you receive.
The exact scope is agreed around your workflow. A typical engagement can include:
- A mapped workflow with clear system boundaries
- Configured integrations and bounded agent tools
- Approval, exception and recovery paths
- Task-based evaluations and operational logging
- A rollout guide and support responsibilities
Illustrative workflow
An incoming customer request
Read the request → find the account → gather missing information → prepare the update → approve → update the CRM.
An example of how this capability can fit a business process.Define what better looks like.
We agree useful measures before implementation and compare them with the current workflow.
- ↗Time spent on the complete workflow
- ↗Exception and rework rates
- ↗Successful, authorised actions in the destination system
Your questions, answered.
How is an agent different from a chatbot?
A chatbot primarily provides a conversational interface. An agent can also select and use tools to carry out tasks. A useful system may combine both, but its permissions need to be explicit.
Do all automated steps need AI?
No. Rules are often more reliable for predictable steps. We use AI where interpreting language, images or variable inputs adds value.
Can this connect to our existing tools?
We assess APIs, connectors, access permissions and data formats for your actual systems before agreeing the integration scope.
Useful before you start
Questions worth exploring.
How to choose your first AI project
Start with work you can observe, data you can access and an outcome you can measure.
AI agents or workflow automation?
Choose the simplest approach that can complete the work reliably. More autonomy is a design choice, not a success metric.
Document automation without losing control
Extraction is one step. Reliable document processing also needs validation, review, integration and a record of what happened.
A useful next step
Bring us the work
that should work better.
One process, one product idea, or a question about where to start.