phase 1 · Discovery
Discover
Turn the brief into a clear document model, visual direction, and measurable first release.
- ↗A bounded brief
- ↗A content and route map
- ↗A first-release decision log
about · services
Focused digital services for teams that need a clear customer journey and a dependable launch.
A focused path from customer need to a dependable digital service. We help teams across the Gulf, Levant, and North Africa launch clear, bilingual experiences without unnecessary complexity.
Clear Arabic and English journeys for campaigns, services, and products. Editors can update content without waiting for a release.
Customer portals, learning services, commerce tools, and internal workflows shaped around how your team actually operates.
Make an existing service easier to use and faster to operate, without forcing a risky rewrite.
delivery phases
Each phase is a Wagtail document with reusable prompts, outcomes, and a clear handoff — all in one place.
phase 1 · Discovery
Turn the brief into a clear document model, visual direction, and measurable first release.
phase 2 · Build
Build the smallest complete path as server-rendered HTML, then add HTMX and Alpine where they improve the document.
phase 3 · Launch
Ship a dependable release with content parity, observability, and a handoff the team can own.
phase 4 · Enhance
Improve the living system through measured content, performance, and interaction enhancements.
We keep the work visible and incremental. Each phase leaves your team with a clearer decision, a working slice, or a useful handoff.
We map the customer, the offer, the languages, and the moments that need to work first.
We turn the direction into a calm interface with clear content hierarchy and a flexible visual system.
We build the first useful slice, connect content, and test the critical path on real devices.
We launch with a performance budget, an editor handoff, and a simple plan for the next market.
AI tools · integrate the ones that earn their place
Every service can ship with the AI surface that fits the workflow — from an in-house MCP server to managed models and self-hosted local inference.
in-house
The monorepo's AI layer: a Model Context Protocol server, a multi-model chat client, and prompt-to-component tooling.
models
Managed frontier models wired through MCP with provider controls, least privilege, and audit trails.
self-hosted
Run inference on your own hardware for data that must never leave the network.
retrieval
Ground answers in your documents with retrieval-augmented generation and clear citation paths.
protocol
The Model Context Protocol connects any LLM to your tools and data — one standard, any provider.
We start with the customer journey, launch a focused slice, and leave your team with the content and tools to keep improving it.
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