AI assistants are the fastest-moving opportunity in business — and the easiest to get wrong. Ours sit on governed data and take only curated actions — never a chat window pointed at a database. Every answer cites its source.
Your business already knows the answer to most questions it asks — it's just spread across systems, reports and the one colleague who's on holiday. So questions become tickets, and decisions wait in a queue.
Generic chatbots don't fix this: an assistant that guesses, or answers from the open internet, is a liability in a governed business.
We build assistants that sit on your governed data and take only curated actions — every answer cites its source, and every permission respects who's asking.
The same pattern serves analysts, operations and customers alike — from chat-with-your-data to a service agent that resolves routine cases end to end.
Answers in seconds where previously a ticket took a day. Decision support without retraining analysts. Customer experience without burning out service teams.
Mid to late maturity. Rewards organisations that already trust their data — an assistant is only as reliable as the foundation under it.
Where this lands in practice. Each row opens with the detail — and what it buys you.
Natural-language analytics on the lakehouse with citations to source rows. Tested against business questions, not toy SQL.
The payoff. The analyst queue shrinks to the questions that deserve an analyst.
A front line that never queues: resolves the routine incidents end-to-end — password resets, order status, refunds within policy — and hands the hard cases to your people with the context already gathered. Your support team stops drowning in tickets and starts handling the ones that need a human.
The payoff. Support volume stops scaling with your customer count.
Conversational SKU discovery, fit / delivery questions, returns prep — grounded in catalogue, stock and policy with full audit logs.
The payoff. The conversion of a good shop assistant, at web scale.
Copilots over content archives, policy docs and analyst libraries. Cite-or-don't-answer pattern.
The payoff. Years of institutional knowledge become something you can ask a question.
Co-pilots for finance, ops and back-office teams — draft invoices, prepare KYC cases, summarise tickets, surface exceptions. Humans approve; the assistant accelerates and never auto-executes irreversible actions.
The payoff. The team spends its day on judgement calls, not copy-paste.
Through the Moberg Delivery Framework — the same five stages, governance and engineering standards we run on every engagement, from business case to long-term run. Microsoft has independently validated our AI practice — table stakes. Judge us on an assistant that cites its source or declines to answer.