AI automation FAQ for small businesses
- Asked on first calls
- 13Q&A
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Answers, first sentence.
Trellient is an AI transformation partner for non-tech businesses — manufacturers, retailers, clinics, and service firms. We start with an audit of your data and workflows, score the opportunities by ROI, then build and measure one automation at a time.
Yes. Trellient exists specifically for teams with no engineers and no in-house data people. We work in the tools you already use, and we train your staff to run what we build.
A readiness and data audit, an opportunity map with every candidate workflow scored by ROI, and one recommended pilot with an expected payback range. It is fixed-price, and the map is yours to keep.
The first working automation usually lands in about 30 days. Typical payback is 4–8 months, measured against the baseline numbers we record before the build starts.
That is exactly what the audit fixes first. Data readiness is step one of the framework: we find what is missing, duplicated, or trapped in paper before anyone writes an automation.
No. We remove repetitive work — copying, chasing, retyping — and keep a person in the loop to approve output. Your team ends up doing the parts of the job that need judgment.
The AI Readiness Assessment is a fixed-price entry point. Builds and retainers are scoped after the audit, because pricing a workflow before seeing the data is guesswork.
Manufacturers, retailers and distributors, clinics, and professional service firms. We are based in India and work with non-tech small and mid-sized businesses.
No. Prices, stock and amounts are always looked up from your own sheet or system. AI only reads messages and writes drafts, and a person approves them until the results have earned trust.
No. Most owners run their business on WhatsApp, so that is where drafts, approvals and a daily summary arrive. A monthly one-page report covers the numbers.
Yes. Each client runs on its own separate setup, so one business's data never mixes with another's.
We test with your real messages — typos, voice-note style and Hinglish included — before anything goes live. When a message can't be read, the system asks the customer again or passes it to you instead of guessing.
Things that rarely pay back for a small business: custom model training, AI search over a handful of documents, voice agents meant to replace your staff, and automated pricing without enough sales data.