DigiLeharBuild for what's next

AI

We build AI that can understand data, make decisions and take action.

Not a chat box beside the real work. AI that acts inside the systems a business runs on, with rules where rules belong and people where judgement is needed.

01 · Agents

Agents that act inside ERP, CRM, WhatsApp and payments.

An agent reads a record, decides what to do, and does it through a controlled set of tools: update the order, send the confirmation, flag the anomaly. Every action is logged. Anything that costs money or reaches a customer can wait for approval.

RecordDecideActLog

In practice

  • Reconcile a payment against an order and mark it complete
  • Send a WhatsApp update when a booking changes
  • Notice a stuck workflow and escalate it to a person

02 · Data intelligence

Records and documents that answer questions.

Invoices, contracts, enquiries, reports. We build systems that read them, structure them, and answer questions with a citation to the source. People stop searching and start deciding.

DocumentsStructureAskAnswer with source

In practice

  • Extract line items from supplier invoices into the ledger
  • Answer 'which enquiries mentioned a deadline this month'
  • Summarise a week of operations from the system of record

03 · Automation

Automations that run without being watched.

An event happens: a payment lands, a form is submitted, a stock level drops. A workflow runs: routes, notifies, reconciles, records. Deterministic where the business needs certainty. AI only where judgement is required.

EventWorkflowDone

In practice

  • Qualify an enquiry and alert the right advisor in real time
  • Confirm a booking to guest and host the moment payment clears
  • Sync a subscription change to access roles

Principles

How we keep it honest.

AI earns its place in a business system by being predictable, measurable and answerable to people. These are the rules we build to.

01

Deterministic where it matters

Billing, access and inventory follow rules, not probabilities. AI sits beside these systems and acts through them. It does not get to improvise inside the ledger.

02

People in the loop

Actions that cost money or reach customers can require approval. The agent proposes, a person confirms, until the system has earned the right to act alone.

03

Data stays with the client

Models run against your data in accounts we manage for you. We do not train on client data, and nothing leaves the system without your say.

04

Measured, not promised

Every AI system ships with evaluation: what it got right, what it got wrong, and how that changes over time. If we cannot measure it, we do not call it done.

In active R&D·Not shipped

Autonomous Operational AI Agents

AI agents that don't just chat. They query databases, reconcile inventory, dispatch WhatsApp notifications and resolve workflow anomalies on their own.

Our own product

The agent runtime we are building for our own products and, later, for client systems.

Where it stands

Work

Automation in shipped systems.

Where event-driven automation is already doing the work in client platforms.

All work

Start a project

Have a process that should run itself?

Tell us what happens today and what should happen instead. We will say whether it needs AI, a rule, or both.

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