AI agents: digital workers for the work that slows you down
We design and deploy AI agents that read, decide and act across your tools, taking on repetitive back-office work and handing exceptions to your team.
Overview
A chatbot answers questions. An AI agent does the work. It reads the invoice, checks it against the purchase order, prepares the entry in your ERP, and asks a person only when something does not add up.
Quibo builds these digital AI workers on leading large language models, connected securely to your email, documents, CRM, ERP and internal APIs. Every agent has a clear job description, a defined set of tools it may use, and rules for when to stop and ask.
Every action is logged, every decision can be explained, and people approve anything that carries real risk. The result is capacity that grows with demand, without adding headcount or cutting corners.
What we offer
- 01
Back-office agents
Agents for invoices, purchase orders, reconciliations, onboarding and data entry across your systems.
- 02
Customer service agents
Agents that resolve routine requests on WhatsApp, email and web chat, and hand complex cases to your team with full context.
- 03
Sales and lead agents
Agents that research, qualify and follow up leads, then keep your CRM up to date.
- 04
Knowledge assistants
Agents grounded in your policies, contracts and manuals that answer with sources, not guesses.
- 05
Multi-agent workflows
Teams of specialised agents that pass work between them, coordinated by clear rules.
- 06
Tool and system integration
Secure connections to ERP, CRM, email, spreadsheets and internal APIs, with least-privilege access.
- 07
Guardrails and human approval
Approval steps, limits, audit logs and escalation rules, designed in from day one.
- 08
Evaluation and monitoring
Test suites, quality scoring and dashboards that show what every agent did, and how well.
How we work
- 01
Map
We map one process step by step and choose the tasks an agent can own safely.
- 02
Design
We write the agent’s job description, tools, guardrails and escalation rules.
- 03
Pilot
The agent works alongside your team, with a person approving each action, while we measure quality.
- 04
Scale
We widen its autonomy where it has earned trust, then add the next workflow.
Related work
All case studiesAccounts Payable AI Worker
A digital worker that reads supplier invoices, matches them to orders and receipts, and prepares them in the ERP for approval.
Read case studyCustomer Support Agent
An AI agent that resolves routine customer requests across channels and hands complex cases to people with full context.
Read case studyLead Research Agent
A digital sales assistant that researches new leads, scores them against your ideal customer profile and drafts personal follow-ups for review.
Read case studyFrequently asked questions
How is an AI agent different from a chatbot?
A chatbot replies in conversation. An agent takes actions in your systems, such as updating records, drafting emails or preparing transactions, within rules you set.
Will agents replace our team?
They take on the repetitive volume so your people can focus on judgement, relationships and exceptions. Most teams use the capacity to grow without adding headcount.
How do you keep agents safe?
Least-privilege access, human approval for risky actions, limits on what an agent can spend or send, full audit logs and regular evaluation against real cases.
Which AI models do you use?
We choose per task from leading commercial and open models, and can use private deployments where data residency matters.
Great products start with a single conversation.
Tell us what you are building and we will tell you honestly how we would approach it. No pitch deck needed, and no obligation.
Start a conversation