Repetitive internal tasks are taking up your best hours
Every business has 10–30 processes that consume 30+ hours of the team’s week: updating prices, syncing data between systems, generating reports, moving information from A to B, answering the same questions every day. Your best people doing a machine’s job.
A well-designed AI agent runs those processes on its own — with judgement, not rigid rules. It gives you back those 30 hours. And your team, their focus.
How we build it
1. Map of automatable processes
Session with your team where we list the real repetitive tasks. We prioritise by: time invested / week, clarity of the process, risk if executed poorly. We leave with an actionable ranking, not a generic analysis.
2. Agent design
Each agent has: a clear objective, tools (APIs it can call), detailed instructions, escalation criteria. We use LangGraph or Autogen architectures depending on the complexity of the workflow.
3. Integration with your stack
The agent connects to the tools you already use: Google Workspace, Slack, Notion, your CRM, your ERP, GitHub, Linear. Without replacing anything — orchestrating what you have.
4. Monitor + guardrails
Every agent action is logged. Critical actions (moving money, sending mass emails, modifying contracts) require human confirmation. The agent acts autonomously where it is safe to do so; it asks for permission where it is not.
Types of agent we typically build
- Pricing agent: monitors competition, proposes adjustments, awaits validation.
- Sync agent: reconciles data between CRM, ERP and marketing tool.
- Proposal agent: generates first draft of commercial proposal based on briefing.
- QA agent: reviews content generated by humans or AI before publishing.
- Operations agent: internal tickets, team assignment, reminders.
When we do NOT recommend this
- If you have no clear repetitive processes: agents don’t invent work.
- If your systems have no APIs (everything is legacy desktop): the agent cannot operate.
- If your team is not willing to trust agents (very controlling culture): the agent goes unused.
The agent is not a black box
Every agent decision is traced: what it evaluated, what it chose, why. Your team can inspect and correct. If the agent decides something odd, you know. If it decides something good, you learn from it.
Stack we use
- LangGraph / Autogen depending on flow complexity.
- Claude 4.5 as the main brain.
- n8n self-hosted for triggers and lightweight orchestration.
- Your own stack (CRM, ERP, SaaS tools) via API.
We start with a diagnostic session
Before quoting the full setup, we run a 90-minute session. We look at your current processes, your tool stack, and the team running them today, and we leave with an honest recommendation: whether this service fits where you are now, or whether it makes more sense to start with something else.
We don’t charge for that session. If you’re interested, get in touch.