Independent AI product studio

Big ideas.
Real systems.
Built for you.

Tagcodi turns complex challenges into useful software. AI products, smarter workflows, and digital platforms built around your business.

Based in Addis Ababa, Ethiopia See the Leafy Green build below

Selected work

Proof, not promises.

Products and systems built around the operational outcome, not a trendy stack or a decorative interface.

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Leafy Green
Client work
Featured build01

Leafy Green

Bring plant shopping and daily order operations into one system.

A storefront with checkout, inventory, orders, and a separate admin panel.

Next.jsPostgreSQLPayments
Client work
Products
02 / case study

Aurora

Reduce the work of publishing across multiple social accounts.

A shared dashboard for creating, scheduling, and managing posts.

Capabilities

Built around the bottleneck.

No fixed playbook. We identify the constraint, design the smallest reliable system, and build toward measurable value.

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01

Applied AI systems

Assistants, retrieval, and decision-support tools grounded in your data and wrapped in operational guardrails.

From prototype to dependable workflow

02

Workflow automation

Connect the repetitive handoffs between people, platforms, and data so the operation moves without babysitting.

Less busywork, fewer dropped steps

03

Product engineering

Focused web platforms, internal tools, mobile experiences, and APIs built for clarity, speed, and maintainability.

Software teams can actually own

04

Data & operations

Dashboards and reporting layers that turn fragmented information into one useful source of operational truth.

Signals instead of spreadsheet noise

About Tagcodi

Close to the problem. Accountable for the result.

Tagcodi is an independent software and AI studio in Addis Ababa, Ethiopia. The studio connects business needs with custom products, automation, and reliable digital systems.

About Tagcodi
How the work feels

Clear at every handoff.

Strong delivery is more than clean code. It is shared context, visible progress, and a system that makes sense after launch.

Understand before building

Map the actual workflow, constraints, and success signal before choosing an implementation.

Show working software early

Replace long speculative phases with tangible checkpoints people can test and challenge.

Leave a system you can own

Clear architecture, documentation, and operational visibility are part of the product.

Field notes

Thinking in public.

Browse insights
Notes are being prepared

Practical writing on AI systems and product delivery.

Open the journal
Next build / available

Bring the messy problem.

In one focused conversation, we can identify the constraint, the smallest useful system, and the right next step.