Connect the tools you have. Add intelligence where it pays.
Your business already uses WhatsApp, a payment provider, a courier, maybe an ERP. We make them talk to each other, and we add AI where it removes real work, not where it makes a demo.
What integration means, and what AI is good for today.
Integration is plumbing: when an order is paid, the courier is booked, the customer gets a WhatsApp message, and the accountant's system gets the entry, with nobody retyping anything. AI is useful for a narrower set of jobs: reading messages and documents, drafting replies, classifying requests, answering questions from your own data. We put it inside the workflow with rules and a human in the loop where money or reputation is involved.
- Staff retype the same information into two or three systems.
- Customers wait for status updates that the system already knows.
- Support answers the same twenty questions all day.
- Documents, invoices or messages need reading and sorting at volume.
A small integration layer in the middle receives events from each service and triggers the next step. The AI assistant sits on the same hub, with access to your data and strict limits on what it may do on its own.
What is included in integrations and AI
Messaging flows
WhatsApp Business API and email: order confirmations, delivery updates, reminders, two-way conversations routed to the right person.
Payments and carriers
Local and international payment providers, courier booking and tracking, reconciliation of what was paid against what was delivered.
ERP and accounting sync
Products, customers, invoices and payments kept in sync with the system your finance team uses, with a log of every transfer.
AI assistants
Assistants that answer from your own data, draft replies, extract fields from documents and hand off to a person when unsure.
How we build integrations and AI
Reliable plumbing first. Models on top, with limits.
- Event-driven hub
- Webhooks and queues instead of polling. Every event is stored, retried with backoff, and visible in a log your team can read.
- Idempotency and reconciliation
- Every outbound call carries a key, so retries never double-charge or double-book. Nightly reconciliation flags mismatches.
- Retrieval over your data
- Assistants answer from indexed documents and database rows with citations, not from memory. Permissions apply to the assistant as they do to a user.
- Guardrails
- Structured outputs, allow-lists of actions, spend limits and a human approval step for anything that moves money or contacts a customer.
- Evaluation
- A test set of real past cases. Every prompt or model change is scored against it before it reaches production.
From a list of tools to a connected business
- Phase 1
Inventory
Which systems exist, who owns the accounts, what data moves by hand today.
- Phase 2
First flow
The one integration that removes the most retyping goes live first, usually payment to courier to WhatsApp.
- Phase 3
Assistant pilot
If AI is in scope, a pilot on one task with a measured baseline: time saved, accuracy, escalations.
- Phase 4
Run and extend
Logs and alerts watched, providers' API changes absorbed, new flows added as needed.
Questions people ask
- Will the AI answer customers on its own?
- Only within limits you set. It can answer known questions and draft the rest for a person to send. Anything involving money or a complaint goes to a human.
- Is our data used to train models?
- No. We use providers with no-training terms, and your documents stay in your own index under your account.
- Which WhatsApp setup do you use?
- The official WhatsApp Business API through a provider, under your own phone number and verified business, so messages are reliable and compliant.
Tell us what you need to build.
A short message is enough to start. We reply within 24 hours.