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AI Agent Development
Agents that reason over business context, call tools, respect approval rules and execute multi-step work.
- Tool calling
- Human approval
- Audit trails
Available for selected projects
AI AGENTS · AUTOMATION · SOFTWARE SYSTEMS
I build AI systems that do real work.
I design practical AI agents, business workflows and production software that connect tools, reduce repetitive work and give teams more operating leverage.
Automation-first
Human-gated
Production-minded
AGENT CONTROL PLANE
READY
AI Agents✦LLMs✦Automation✦TypeScript✦Next.js✦NestJS✦Python✦PostgreSQL✦Redis✦APIs✦Docker✦Security✦
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WHAT I BUILD
Technology tied to business outcomes.
I focus on useful systems: fewer manual handoffs, cleaner data flow, faster response times and controlled automation.
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Business Automation
Connect repetitive workflows across email, forms, spreadsheets, CRMs, queues and internal systems.
- Workflow mapping
- Event actions
- Error recovery
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Custom Software Systems
Web interfaces, backend services and APIs designed around operational requirements instead of generic templates.
- Web apps
- Backend APIs
- Data workflows
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AI Integration & Orchestration
Connect models, tools and private business data behind a controlled integration layer with fallbacks.
- Model routing
- Structured output
- Fallbacks
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Operations Automation
Automate reporting, triage, document processing, dispatch and other repeatable operational tasks.
- Queues
- Schedules
- Notifications
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Architecture & Consulting
Technical design that balances delivery speed with security, maintainability and future scale.
- System design
- Security review
- Delivery plan
AI-firstArchitecture
API-drivenIntegration
Human-gatedCritical actions
Audit-readyWorkflows
SELECTED WORK
Systems built around real operational problems.
These projects show the kind of architecture I work on: logistics, governed decision systems, security and AI-assisted operations.
AI-Agentic Smart Logistics OS
A modular logistics platform spanning inventory, orders, shipments, dispatch, drivers, payments, approvals, audit and an AI control plane.
Role-based operationsQueue-driven workflowsAI approval layer
Build something similar ↗
CrediPass Nigeria
A governed credit-passport and risk-evaluation platform built around masked identity data, consent, auditability, deterministic contracts and secure API workflows.
Masked identityConsent controlsRisk evaluation
Discuss governed automation ↗
Nissi-AI Cyber Defense
An AI-assisted endpoint and network-defense concept combining monitoring, governed analysis and operator-controlled response workflows.
Endpoint telemetryNetwork monitoringOperator approval
Discuss defensive AI ↗
PRACTICAL AI AGENTS
Give AI tools, rules and responsibility.
A useful agent is more than a chat window. It needs business context, controlled tool access, approval boundaries, recovery paths and logs you can inspect.
Inbox triageDocument processingLead qualificationCRM updatesReport generationInternal searchCoding & ops assistanceMulti-step workflows
AGENT WORKFLOWGOVERNED EXECUTION
01InputEmail · Form · API · Event
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02Reasoning + ToolsRetrieve · Classify · Plan
↓
03ApprovalPolicy · Human gate · Limits
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04ActionUpdate · Send · Create · Execute
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05AuditLog · Trace · Measure
WHERE AUTOMATION PAYS
Turn recurring work into reliable workflows.
Typical automation targets are repetitive, rules-driven, time-sensitive or spread across too many tools.
Sales & Leads
Capture, enrich, qualify, route and follow up without losing context between tools.
Documents
Extract information, classify files, generate structured summaries and trigger next actions.
Operations
Coordinate queues, alerts, approvals, dispatch, reporting and exception handling.
Internal Knowledge
Search company information and return grounded answers with clear source boundaries.
ABOUT
Technical depth without unnecessary complexity.
I work at the intersection of AI agents, backend engineering and business automation. My focus is dependable execution: systems with explicit permissions, observable workflows, maintainable architecture and clear boundaries around what automation should do on its own.
I use AI as an operating layer—not as decoration—combining models with APIs, data, queues, approvals and software contracts so the result can fit real business processes.
01 Make it useful02 Make it observable03 Make it maintainable04 Make it secure
HOW I WORK
From problem to production.
A structured build process keeps the business requirement, architecture and implementation connected.
- 01
Discover
Map users, workflows, systems, constraints and success criteria.
- 02
Design
Define architecture, data boundaries, permissions and approval rules.
- 03
Build
Implement the core system with testable contracts and clean interfaces.
- 04
Integrate
Connect models, APIs, data sources and operational tools.
- 05
Improve
Measure results, inspect failures and evolve the system deliberately.
START A PROJECT
Have a workflow that should be smarter?
Tell me what is slowing the business down, what systems are involved and what a successful result looks like.
✓ AI agents & automation✓ Web/backend platforms✓ API & systems integration✓ Technical architecture