Task agents
Agents that follow a defined multi-step workflow and use only the tools and actions they are permitted to access.
Agentic AI · Lagos, Nigeria
Agentic AI systems that move real work forward.
Build controlled agents and assistants that understand a defined task, use approved information and tools, prepare actions, and keep people in control of important decisions.
Where AI can help
Start with a repeatable task, not an AI slogan.
The strongest opportunities are usually clear but time-consuming: repeated enquiries, document-heavy intake, manual summaries and reporting, or useful knowledge scattered across approved sources. We map the task, its risks, and its decision points before deciding where an agent should act and where a person must approve.
What we build
Useful agents with boundaries you can understand.
Every system is designed around explicit permissions, observable steps, and the level of human review the work requires.
Knowledge assistants
Assistants that find and synthesize information from approved business sources with clear references and limits.
Document workflows
Intake, extraction, classification, and routing for repeatable document-heavy processes.
Enquiry triage
Structured classification and response preparation that helps a person review and handle incoming requests faster.
Triggered reporting
Scheduled or event-based workflows that collect approved inputs and prepare useful summaries for review.
Controls and fallback
Human approval points, scoped permissions, evaluation checks, audit visibility, and fallback behavior when confidence is low.
How we deliver
Controlled from the first workflow map.
- 01
Define
Choose the task, boundaries, acceptable actions, and human approval points.
- 02
Prepare
Identify suitable data, approved tools, permissions, and safe test cases.
- 03
Build and evaluate
Implement the workflow, measure outputs, and test failure and fallback paths.
- 04
Launch and monitor
Release carefully, observe real use, and improve the system within defined limits.
Relevant work
Applied AI in a product already running.
Mungo Park
NKAVO built the ingestion, AI summarisation layer, and analytics dashboard for a live WhatsApp community product—and continues to operate it.
Visit Mungo Park →Questions
What responsible AI delivery requires.
How is an AI agent different from a chatbot?
A chatbot mainly exchanges messages. An agent can follow a defined sequence, use permitted tools, prepare or perform approved actions, and return evidence of what happened.
What data do we need?
That depends on the task. We identify the smallest set of approved, relevant information required and test its quality before relying on it in a workflow.
Where does human oversight fit?
We set human approval points according to risk. Important, sensitive, or low-confidence actions can be held for review, while routine steps remain observable and reversible where possible.
Related services
Build the product around the intelligence.
Which repeated task should your team stop doing by hand?
Describe the workflow, the inputs, and the decisions involved. We’ll help you identify where an agent is useful—and where it is not.