Give repetitive work a better way through.
Agents and automation give repetitive work a better way through your business. An automation moves information between systems and applies rules you have agreed. An AI agent goes further: it reads documents, drafts replies, classifies requests or decides the next step, and hands anything uncertain to a person.
Most of the value sits in ordinary work: answering the same questions from customers, pulling details out of documents, re-typing information from one system into another, or preparing a first draft that someone then checks. I design these workflows around the tools your team already uses, with clear points where a person reviews or approves the output.
Every workflow is tested against real examples before it goes live, including the awkward cases: incomplete information, unusual requests and the moments when a connected system is unavailable. You get documentation, a walkthrough and an agreed support scope, so your team can own what has been built.
Discuss agents & automationTeams handling repeated enquiries, documents, knowledge requests or handovers between systems.
- The same enquiries are answered by hand every day
- Staff re-type information from one system into another
- Answers are buried across documents, emails and shared drives
- Routine drafts such as quotes and reports take hours to prepare
- Work stalls when one person is away
- Discover. Map the workflow and agree where a person must approve the output
- Design. Prototype the assistant or automation with representative examples
- Build & validate. Test expected and exceptional cases, then connect it to your systems
- Launch & hand over. Launch with monitoring, documentation and a team walkthrough
- A mapped workflow with explicit human approval points
- An assistant or automation connected to agreed systems
- Evaluation examples covering expected and exceptional inputs
- Operational documentation and an agreed handover
- An assistant that drafts replies to common enquiries for approval
- A document assistant that answers questions from your own policies
- Extracting details from forms, invoices or applications
- Routing and summarising new leads into your CRM
- Preparing first drafts of proposals or reports
Common examples. Your own starting point is agreed in a first conversation.
Which actions can run automatically?
Who reviews uncertain or sensitive outputs?
What should happen when a dependency fails?
Final deliverables and acceptance criteria are agreed around your brief.
Automation projects are scoped per workflow. The proposal sets out the build, the testing, any running costs for AI services and the support that follows launch.
Ask DavendraWhat is the difference between an AI agent and automation?
Automation follows fixed rules, such as copying a form into a spreadsheet. An AI agent can interpret content, for example reading an email to decide what it is about and drafting a reply. Most useful workflows combine both, with a person reviewing anything uncertain.
Will an AI agent act without anyone checking?
Only where you have agreed it can. Each workflow defines which actions run automatically and which need a person’s approval. Sensitive or uncertain outputs are routed to someone to review.
Can it work with the software we already use?
Usually, yes. Most business tools can be connected through their APIs or integrations. Where a system can’t be connected safely, I’ll say so during scoping.
What does it cost to run once it is built?
AI services are generally charged by usage. The proposal estimates running costs from your expected volumes, so you can judge the return before committing.
What happens if something goes wrong?
Workflows are built with failure handling, logs and a clear route for a person to take over. Monitoring and support responsibilities are agreed before launch.