Custom ERP · Your own AI
We build a private AI agent into your ERP and connect it to WhatsApp and Telegram — so answers, approvals and follow-ups happen where your team already works, on your data, with your permissions.
Two views of the same ERP
Which orders are late? On the left of this switch, a report and a spreadsheet. On the right, a sentence.
| Order | Customer | Promised | Status |
|---|---|---|---|
| SO-2291 | Shree Traders | 17 Sep | To deliver |
| SO-2288 | Patel Agro Inds. | 14 Sep | To deliver |
| SO-2285 | Om Jewels | 12 Sep | Partly delivered |
| SO-2279 | Krishna Polymers | 18 Sep | To deliver |
| SO-2276 | Nilkanth Exports | 11 Sep | To deliver |
| SO-2270 | Ambica Steel | 19 Sep | To bill |
Showing 6 of 14 rows · Page 1 of 3
What it takes to get the answer
And the customers with late orders still have not heard from anyone.
Illustrative example with sample data — parties and figures are invented.
What changed
Illustrative example with sample data — parties and figures are invented.
ERP without AI vs ERP with AI
Same modules, same data. The difference is how much of the work still needs a person to go and find it.
| Task | ERP without AI | ERP with AI |
|---|---|---|
| Getting a number | Open the reports menu, set five filters, export to Excel, build a pivot. | Ask in English, Hindi or Gujarati. The answer arrives with the report it came from. |
| Approvals | The approver has to log in at a desk. Purchase orders wait while they travel. | Approve or reject from WhatsApp or Telegram, recorded in the ERP audit trail. |
| Payment follow-up | Accounts runs an ageing report, then calls or messages each party by hand. | Reminders go out by ageing bucket with the invoice attached; replies are logged. |
| Paper bills and challans | Typed in line by line, then checked again by someone else. | A photo becomes a draft purchase invoice, matched to the PO, waiting for review. |
| Stock problems | Discovered at the month-end count, when the order is already late. | An alert the day an item crosses reorder level or stops moving. |
| Daily MIS | Someone compiles the same spreadsheet every morning. | A digest per role, delivered at 9 AM, with a follow-up question one message away. |
| Customer order status | The customer calls, sales checks the ERP, then calls back. | The customer asks on WhatsApp and gets the live status, or a person when needed. |
Three ways in
Start with one. They share the same agent, the same permissions and the same audit trail, so adding the next is configuration rather than a new project.
An AI agent built around your ERP's data model, running on your servers or your private cloud — it answers questions, drafts documents and takes approved actions with the same permissions as the person asking.
Learn moreOrder confirmations, dispatch updates, payment reminders, approvals and a customer-facing AI assistant — all on the official WhatsApp Business API, all written back to the ERP.
Learn moreA Telegram bot for your team: daily MIS in topic groups, exception alerts, one-tap approvals and an AI agent that answers ERP questions — free to run, with no per-message cost.
Learn moreYour own AI
On-premise, private cloud or your own model account. Never a shared multi-tenant chatbot.
The agent sees exactly what the person asking can see, and nothing more.
Every answer names the report or query behind it. No verified data, no answer.
The agent drafts; people submit. Every action is in the audit trail.
ERP automation
The ones clients ask for first. Each is a trigger in the ERP and an action on the right channel — and each can be switched on alone.
How we deliver it
We sit with owners and department heads and list the questions they ask, the approvals they chase and the messages they send every week.
A controlled API layer over your ERP — ERPNext, the Samarth ERP Platform or your custom system — with role-based access and logging.
On-premise open-weight model, private cloud or a hosted model under your account, decided per workload by sensitivity and cost.
WhatsApp Business API numbers and templates, Telegram bots and groups, email — each automation pointed at the right people.
One department uses it for real for two to four weeks. We tune answers, thresholds and wording on their feedback before widening.
Remaining teams onboarded in their own language, with usage reviewed monthly and new automations added as the questions change.
Questions
Bring the three questions you ask most often. We will show you what they look like asked of an agent — and tell you honestly which ones your data can answer today.