Practical AI-enabled business systems.
Useful value early. Process and data confirmed. The right system, evolved in stages around real work.
Salix AI (Pty) Ltd is a consultancy based in Johannesburg, South Africa. Salix AI helps businesses solve operational problems. We create value early, confirm the process and data, and then evolve the right system in practical stages: better spreadsheets, apps, automations, dashboards, AI workflows, custom software, or hybrid architecture, using platforms such as Microsoft’s Power Platform where they fit.
AI makes software easier to build. It does not make business systems easier to operate.
That distinction shapes everything we do: how we choose what to build, how we build it, and what happens after go-live.
How we work: Diagnose, Design, Deliver, Operate
Diagnose
Salix starts with the operational problem, not the tool. Where is work slow, manual, risky, or hard to see? The AI & Systems Opportunity Review is the usual entry point: a short, structured diagnostic that identifies the next useful improvement, which is not always an app..
Design
Before anything is built, we confirm the process and the data. That means agreeing how the work should actually run, sorting out the numbers people rely on, and choosing the right stage of system for where the organisation is now: sometimes a better spreadsheet or operating rhythm before any software.
Deliver
We create useful value early and mature the system in stages. AI-assisted development shortens the path to a working system, but production still demands engineering discipline: code review, testing, security checks, documentation and deployment control.
Operate
Systems earn trust in operation, not at launch. We monitor, patch and improve what we build. For AI workflows we also maintain the context, traces and private evals that show the system is still doing its job as models, prompts and data change.
Where to start
AI & Systems Opportunity Review
- A structured diagnostic that identifies the next useful operating improvement, and what it is worth, before you commit to a build.
- Duration line: 1–3 weeks · fixed-scope diagnostic, ending in a findings pack, a staged-value recommendation and a first-90-day plan.
AI-Native App POC
- A focused working prototype that tests whether a clear workflow should become a production system – ending in a real stop, iterate or build decision, not a demo that gets quietly shelved.
- Duration line: 2–4 weeks · working prototype with a documented decision at the end.
Operational DNA Assessment
- Operational DNA helps organisations turn scattered knowledge, templates, processes, and decision habits into reusable AI-assisted workflows. The assessment maps where yours lives and what is worth making reusable first: proposals, onboarding, handovers, status reporting, decisions, quality review.
- Duration line: 1–2 weeks · structured assessment.
Evidence from delivered work
Risk monitoring application · a global bank
A first working version was in users’ hands within two weeks; full deployment across seven reporting teams followed in twelve. The system is now the trusted source of risk-check data for more than 1,200 users, and it remains live and actively maintained.
Digital application process · a talent-development company
The learner portal captured 277 applications digitally at go-live. Three connected applications now run the process, with 60% less manual data entry and surge staffing eliminated entirely.
Municipal bill intelligence · a national utility-management
AI extraction reads inconsistent municipal bills, with every result confirmed through human review and accuracy measured per bill. The system is evolving in deliberate stages: extraction and review live in production, tariff intelligence in build.
Much of this work runs inside Microsoft estates: apps and workflows built on Microsoft's Power Platform, Power BI reporting and Microsoft 365 integration, alongside custom web systems where they fit better. Read the case studies →
Go-live is the halfway point
Almost anyone can now get a demo working. Keeping a system correct in production is a different job: monitoring, patching, security updates, data quality, and, for AI workflows, knowing whether the answers are still trustworthy as models, prompts and data change.
Salix AI designs for operation from the start: documentation, tests, traces, and private evals: your organisation’s own examples and expected outputs, not public benchmarks. And we operate what we build: the systems we deliver are monitored, patched, and improved on a disciplined rhythm after launch, so they keep earning their place in the business.
Start with an AI & Systems Opportunity Review
Every engagement starts the same way: a paid, fixed-scope diagnostic of one to three weeks. You leave with a diagnostic findings pack, a staged-value recommendation, and a first-90-day plan you can act on, with us or without us.
info@salixai.com · +27 686 474243
