SABRO Assistant connects the knowledge, tools, and operational data your business already has (your ERP, your channels, your people, your history) and produces a grounded daily picture for leadership and an action list for each manager. Ask it a question and the answer comes from your operational reality, not a generic model guessing at your business.
Currently in private beta with a small number of operations-heavy SMEs. SABRO Assistant drafts and surfaces; a named operator approves anything before it leaves the business.
Why generic AI falls short here
You've watched the demos. You've tried a chatbot or two. The model can talk; that was never the problem. The problem is that it doesn't know what's in your ERP, what was said on yesterday's call, what's stuck in dispatch, or what a salesperson promised a customer last week.
"Most 'AI for SMEs' tools sell a chat window. The work of connecting it to anything useful is still on you." The gap SABRO Assistant is built to close
How it works
SABRO Assistant sits between your data sources and the person asking the question. It holds the operational context, retrieves the right information for the right question, drafts a usable answer, and shows its working.
ERP records, CRM records, call summaries, authorised channel signal, spreadsheets, and knowledge documents. SABRO Assistant reads what's already there rather than asking you to re-enter it somewhere new.
Records, commitments, and conversations are held as operational context (who said what, what was promised, what's outstanding), not a pile of unlinked documents. This is the knowledge vault: process notes, vendor terms, and standard practice that used to live in a few people's heads.
Leadership gets a daily briefing. Each manager gets their action list. Ask a direct question and the answer is drafted from the connected sources, with the supporting records surfaced alongside it, not just an assertion.
"Who haven't we delivered to this week, and what did we promise them?"
SABRO Assistant pulls dispatch records from the ERP, cross-checks them against customer commitments captured in channel signal, and drafts a list in the exact words used in the original commitment, ready for a manager to act on, not a screen to interpret.
Operator-approved by design. SABRO Assistant does not take action against the outside world on its own. It surfaces, drafts, and routes; a named operator approves any outbound action before it leaves the business.
What you get
A single grounded picture of what happened, what didn't, and what's still outstanding, drawn from the ERP, call summaries, channel signal, and CRM, not reconstructed from memory at the end of the day.
Each manager sees the actions they own, drawn from the same grounded context, not a general summary they have to interpret for themselves.
Ask a plain-English question and get an answer grounded in your own operational reality, with the supporting records shown, not the internet's best guess about a business it has never seen.
Process notes, vendor terms, standard practice, and the memory that usually lives in a few people's heads, captured into a knowledge vault a new manager can ask questions of, instead of asking "how did we do this last time?"
Breadth grows with each pilot. Joining early access means helping decide which sources and workflows are connected first.
An honest fit check
SABRO Assistant is designed with a strict separation between reading and acting: it can read your business systems and draft an answer, but it cannot message a customer or change a customer record without explicit operator approval. Write-back into business systems is scoped per pilot and enabled only where the integration and approval rules are agreed during onboarding. Data is held per business with isolation enforced from the first row. Formal certifications are not in place during private beta; a compliance roadmap publishes when the product moves beyond it.
Early access
SABRO Assistant works against pilot use cases today; the breadth of sources and workflows it can ground answers in grows every month. Joining early access means:
Or write to hello@makh.ai. Tell us your industry, the systems you already run, and the question you most wish you could just ask.