We build the operating layer complex businesses run on.

Workflows, data, inventory, approvals, and decisions belong in one coherent system rather than spread across eleven tools and a spreadsheet nobody owns. We build that system, and it hands back the hours, the margin, and the headroom that manual work was consuming.

First conversation is 30 minutes and is mostly us asking how the work actually moves.

The cost

Complexity never stays inside one tool.

Growth adds products, locations, approvals, vendors, and exceptions. When the systems underneath do not evolve with it, your team absorbs the difference. That cost never appears as a budget line. It appears as overtime, as delay, and as figures nobody fully trusts.

Fragmented records

The same operational fact lives in four places and none of them agree. Two departments quote different figures for the same month and both can defend theirs.

Manual coordination

Approvals, handoffs, and follow-ups run on people remembering the next action. It works until volume rises, then it quietly stops working.

Delayed visibility

Leaders see the state of the business after reconciliation, once the decision window has already closed. So the call gets made on instinct.

Rigid workflows

Off-the-shelf software handles the common path and breaks around the rules that make your business worth running. Those rules are not edge cases.

Three systems already in production.

One engineering foundation

Each product reuses the same core, so a new system starts further along than a build from scratch would.

Depth over coverage

Every product stays deep in a single operation rather than being stretched to handle every case badly.

Running, not planned

All three are in production with clients today. None of this is a roadmap description.

MachERP finance dashboard showing revenue, margin, working capital, and module health

FinanceProcurementProductionInventorySalesCompliance

What it covers

We already understand how your industry runs.

Every sector has one thing generic software gets wrong. In pharma it is that formulation intelligence belongs in the same system as the batch record. In field service it is that the van is a stockroom. Open the sector you know and you should recognise the problem in the first line, and see what we would build to remove it.

The business is the source model.

We shape the system to how your operation already runs, not the other way round. Four ways in, depending on how well the problem is understood, and engagements move between them, because a review that finds the real constraint usually turns into a build.

All solutions
approvalvendorinventoryinvoiceshiftbatchretainerledger

Your operationthe system built to fit it

What removing manual work actually returns.

₹1.5 lakhper month, recurring

One client's monthly salary cost fell by 1.5 lakh once the manual coordination they had been paying for was automated. That is 18 lakh a year, and it recurs for as long as the system runs.

Salary was the measurable part. The larger return was the time it gave back to people who had been holding the process together by hand.

500+Workflows digitised and automatedAcross the three products and the custom systems we have built.
3Systems live in productionMachERP, Mach Media, and Mach SIMS, all running with clients today.

The intelligence layer runs on your own infrastructure.

How we work

Logic first

Structured data, business logic, workflow and controls solve the operating problem on their own. That is where every build starts, because the rules, permissions, validations and exceptions are what actually encode how your business runs. A model cannot infer them from your data, and it should not be asked to. Intelligence is a layer we add on top where it earns its place, and the system underneath stays complete without it.

Local by default

Where prediction or retrieval genuinely helps, we run it on infrastructure you control. Your costing, your margins, your vendor terms and your customer records stay inside your own environment rather than being posted to a third-party endpoint you cannot audit or switch off. Local models take longer to stand up. They are also far easier to defend to a board, an auditor, or a customer who asks where their data went.

Answerable, not “compliant”

Under the Digital Personal Data Protection Act, the substantive obligations become enforceable from May 2027, with penalties reaching 250 crore. We build so those obligations are answerable: a record of what personal data is held and why, who accessed it and when, consent and retention tracked as part of the workflow, and deletion that is a system function rather than a manual scramble. Compliance is a legal determination and no software can grant it. What software can do is make every answer retrievable on demand.

May 2027Substantive obligations enforceable
₹250 croreSchedule 1 penalty ceiling

Every stage ends with something running.

There is no discovery phase here that produces only a document. Each stage ends with software you can use.

  1. Operating model

    Model the operation

    We map how work actually moves: roles, rules, decisions, dependencies, controls, and the exceptions everyone works around. Documented as it is, not as the process document claims.

  2. Working software

    Engineer the system

    That operating model becomes software: structured data, automated workflow, controls, and reporting. Built in deployable stages so value arrives before the full scope is complete.

  3. Connected operation

    Connect and retire

    We integrate the tools worth keeping, switch off what holds the business back, and leave room for the system to keep changing as the operation does.