Deployment shape · Anonymous
When the customer-facing motion runs end-to-end on one platform.
Some Fairshift deployments go four layers deep. Field app for the team in the warehouse. Operations dashboard for HQ. Customer-facing voice and WhatsApp. Vendor and contractor workspace. Same platform underneath. This is the shape of one.
Four apps. One platform underneath.
A deep deployment is rarely one app. The customer-facing channels need an operations layer behind them. The HQ dashboard needs a field app feeding it. The vendor side needs a workspace that talks to all three.
Field mobile app
An Android app for field teams. They add weight slips, photos, and new stock. It works offline, uses local languages, and saves GPS.
Operations dashboard
A main office view of stock, work, and quality at each site. The agent answers work questions in plain words.
Customer-facing channels
Use voice, WhatsApp, and web chat for buyer questions. One agent remembers each talk and replies in the buyer's language.
Vendor & contractor app
A simple space for contractors and vendors. They can add deliveries, check payments, and talk to the main office on WhatsApp.
Live in weeks, deeper every month.
This is not a six-month setup. Customer channels go live in week one. The field app, vendor space, and work view follow over the next few months. The business teaches Fairshift how its work gets done.
Basic AI may answer a few questions. Fairshift answers ten thousand.
A basic AI tool soon runs out of answers. Real work has site rules, quality levels, many steps, and vendor terms. Fairshift can answer because the work data lives in the platform itself.
The data is the platform's data.
When operations live on Fairshift, the agent answers from primary records, not from a snapshot pulled into a vector store.
Reasoning over real workflows.
Quality grades, multi-step processing, recursive transforms - the agent reasons over them because they're modeled, not sketched in a prompt.
Context that compounds.
Every interaction across every channel adds context. The agent your customer talks to next week has read every interaction up to now.
Want a deployment this deep?
Tell us your industry and the operational questions a generic AI can't answer. We'll show you a path to a deployment that does.