Business Solutions
How the Awee Skills Engine companions people and workers with the automations they actually need.
Most digital work is repetitive, structured, and dull — but it still requires a human to initiate it, review it, or act on the result. The Awee Skills Engine is built to handle that layer: the daily automations, data tasks, and process steps that sit between people and the systems they work with.
What we're building
The engine is designed to companion people at work — not replace workflows wholesale, but fill in the gaps: the export someone runs every morning, the document that needs reformatting before it can go anywhere, the approval that sits in an inbox because there's no better place for it, the report that gets manually assembled from three different sources every Friday.
These are not grand enterprise integrations. They are niche, common, often tedious — and they are everywhere. Some are pure data tasks: transforming a file, calling an API, populating a record. Others involve a human at a specific point: a decision, a review, a sign-off. The engine handles both, and the handoff between them.
The goal is a toolbelt. A set of components — built-in and custom, AI-assisted and deterministic — that any worker can reach for when they need to automate something, process something, or interact with a system in a structured way. Not a no-code toy. Not an enterprise platform. Something closer to a skilled colleague who knows how to operate all the software.
The interaction layer
Right now, business functions built on the engine are surfaced as web UIs: tables, forms, dashboards, action queues. The data people need is there; the actions they can take are wired to the automations behind them.
Desktop, mobile, and wearable interfaces are on the roadmap. The engine does not care how a workflow is triggered or how its results are surfaced — that is a presentation layer concern. The same automation that a finance manager initiates from a browser could eventually be triggered from a phone, confirmed from a watch, or run on a schedule with no interface at all.
Where we are now
We are building out the engine by solving specific cases end-to-end. Right now that means a CRM for managing contacts and pipelines, and banking XML bulk payment file generation for finance teams handling payments across multiple payees. Invoice ingestion is next.
Each case is chosen because it produces components that generalise. A validated, structured file export is useful beyond payments. A record-matching step is useful beyond CRM. A human approval gate works the same way regardless of what is being approved.
Awee Skills Engine is the lego for AI-powered adults. Every component is a brick. Every workflow is something you build with them. The library grows with every case we solve.
What this looks like in practice
The range of things the engine can handle is deliberately broad:
- A field worker submits a job report from their phone; the engine structures it, attaches it to the right client record, and fires a billing workflow
- A team receives a weekly data export from a supplier; the engine normalises it, flags anomalies, and loads the clean records into the working dataset
- A manager needs sign-off from two people before a payment runs; the engine routes the request, waits, and proceeds only when both approve
- An AI model extracts line items from an incoming document; a human reviews the result before it is posted
- A recurring task runs every morning, pulls data from three sources, and drops a structured summary where the relevant person will see it
None of these require a bespoke integration. They require components, wired together, with the right human touchpoints built in.
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