We design, build, and integrate AI agents that take on repetitive workflows, work inside the tools your team already uses, and hand decisions to your people where judgment matters.
Your team answers the same questions and fills in the same forms every day.
Leads and requests wait in an inbox until someone has time to triage them.
Information sits in documents, chats, and tools that can't be searched together.
Routine handoffs between systems depend on someone copying data by hand.
Illustrative examples of the agents we build. Each one is scoped to your workflows and tools, and which ones make sense comes out of a discovery conversation — this is not a catalogue to order from.
Leads go cold while the team is busy with admin.
Agents that qualify inbound enquiries, log and enrich them in your CRM, draft follow-ups, and prepare context before a call. Your sales team reviews what goes to customers and owns every deal conversation.
Repeat questions fill the queue and slow down the complicated cases.
Agents that answer common questions from your approved knowledge base, collect the details a case needs, and route the rest to the right person with context attached. Sensitive or uncertain cases are escalated to your team rather than guessed at.
Routine admin runs on copy, paste, and reminders.
Agents that handle requests such as data entry, document preparation, status updates, and approval routing across your systems — with an audit trail and a human sign-off on steps that carry risk.
The answer exists somewhere, but finding it takes asking a colleague.
Assistants that answer staff questions from your own documents, policies, and records, and show the sources they used so people can verify before acting.
A phased approach with your team involved at each stage. Scope and timeline are set in the proposal after discovery.
We map the workflow, the tools involved, and where an agent can help — and where it shouldn't act alone. You get a clear scope, success criteria, and the points that need human approval.
We design the agent's behaviour and connect it to the tools you already use — CRM, email and messaging, helpdesk, documents, spreadsheets, and internal systems — through their APIs or the integrations they support.
We test on real scenarios with your people in the loop, review edge cases, and set the guardrails: what the agent can do, what it must escalate, and what it logs.
We deploy in stages, help your team work alongside the agent, monitor how it performs, and keep refining it against how it is actually used.
Only the ones you approve. We define what an agent can do independently, what needs a person's sign-off, and what it must escalate. AI agents can make mistakes, so we design for review, logging, and easy human override rather than promising perfect autonomy.
In most cases, yes. We connect agents to systems such as your CRM, email and messaging channels, helpdesk, document storage, and internal tools, using their APIs or supported integrations. Part of discovery is checking what each of your tools allows.
A clear picture of the workflow, access to the relevant tools in a test environment, and a point person on your team who knows how the work is done today.
We limit what an agent can access to what the task needs, and we agree how data is stored and processed before building. Data-handling requirements are part of the scope discussion.
It depends on the workflow and the tools involved. After discovery, we give you a specific scope and timeline in the proposal.
Tell us what your team handles manually and which tools you use. We'll help you work out whether an AI agent is the right solution and what it would take to build one.