SmartLink
AI & automation

Business process automation services in Pakistan

Business process automation services in Pakistan are usually requested as a tool purchase and delivered as a process argument, which is the right way round. SmartLink Services maps the work first from Karachi, with real times and real volumes, removes the steps that should never have existed, then automates what is left using rules where rules will do and a model only where they run out. Below is the commercial detail. What automation costs at market rates, how long a first automation takes to reach production, and the discipline that saves clients the most money, which is deleting the step instead of automating it.

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Start
Process mapping
Mix
Rules + AI where needed
Measure
Hours returned
Overview

Automating a bad process only makes it fast.

Automation requests usually arrive with a solution attached. Somebody wants a bot to copy figures between two systems, or an approval chain rebuilt in a workflow tool, or a reconciliation that currently takes two days done overnight. Sometimes that is the right answer. Often the step being automated should not exist, or exists because a system limitation was worked around years ago and the workaround outlived the limitation by a decade.

So the first piece of work is mapping the process as it actually runs, with times and volumes, rather than as the procedure document describes it. That means sitting with the people doing it. What emerges is usually a shorter process than anyone expected, plus a set of steps that exist for no current reason: an approval that has never rejected anything, a report produced for somebody who left, a spreadsheet maintained because a system field was full.

What remains gets automated with the simplest mechanism that works. Deterministic rules where the logic is deterministic, because rules are testable, explainable and cheap to run. A model only where the input is genuinely unstructured or the judgement is genuinely fuzzy. And an exception path with a named owner, because every automation meets a case it cannot handle, and the ones without an owner fail silently.

Scope

What Process automation covers

Everything below is agreed in writing before any ai solutions work starts, so both sides know what is in and what is not.

What the work covers

  • Process mapping with time and volume measurement
  • Elimination of unnecessary steps before automation
  • Approval workflow and notification automation
  • Reconciliation and matching automation
  • Exception routing to named owners
  • Before-and-after time saving measurement

What you get at handover

  • Process maps, current and target
  • Deployed automations with owners
  • Exception handling procedure
  • Time-saving measurement report
  • Support and change procedure

Typically involves

Power Automate ERP workflow engines SQL
Discuss this service
01

Map the process that actually runs

Procedure documents describe the intended process. The real one contains a spreadsheet that three people maintain, a chat group where exceptions are agreed, a step that is skipped when the month end deadline is close, and one person who knows how to handle the awkward supplier. Automating from the document produces something that handles the ordinary path and breaks on everything the document never mentioned, which is where most of the effort actually goes.

We map by observation and interview, recording who touches each step, how long it takes, how often it occurs, and how often it comes back for rework. Rework volume is the most useful figure and the one nobody has, because it points at where the process is failing rather than where it is merely slow. A step taking twenty minutes once a week matters less than a five minute step done two hundred times with a fifth of them returning.

The map also has to record decision authority honestly. Who approves, and who actually approves when that person is travelling. Systems tend to encode the official answer, and the official answer is why people share credentials. If a process depends on delegation, temporary authority or a tolerance a supervisor applies informally, the automation has to model that explicitly or it will be worked around within a month of going live.

  • Process observed and timed as it runs, including the spreadsheets and the chat groups
  • Volume and rework rate recorded per step, since rework points at the real problem
  • Actual decision authority captured, including delegation and informal tolerances
  • Exceptions catalogued by type and frequency rather than treated as one category
  • The map agreed by the people who do the work before anything is designed
02

Remove steps before you automate them

The cheapest automation is deletion. Approvals that have never rejected a transaction in living memory are a control in name only, and replacing them with a tolerance rule and a sampled review gives you a real control while removing a queue. Reports nobody opens can be stopped, which is easy to establish if the system logs access. Data entered twice into two systems is a case for an interface rather than for a bot that types faster than a person.

Questioning steps needs care and it needs the right people in the room. Some steps that look pointless are carrying a regulatory requirement or an audit expectation that is not written on them anywhere. The test we apply is simple: what happens if this step is removed, who would notice, and what would go wrong. If nobody can answer, the step is a candidate. If the answer is a real consequence, it stays and gets automated properly.

What comes out of this is usually a smaller automation scope and a better process, which is a less impressive project and a more valuable outcome. It also changes the business case honestly. Time saved by deleting a step is saved permanently and costs nothing to maintain. Time saved by automating a step requires an automation that somebody has to own, monitor and repair when the systems underneath it change.

  • Steps tested against what would actually go wrong if they were removed
  • Approvals that never reject replaced by tolerance rules with sampled review
  • Duplicate data entry treated as an integration requirement rather than an automation target
  • Reports and outputs stopped where access logs show nobody uses them
  • Savings from deletion reported separately from savings that carry a maintenance cost
01

What process automation costs in Pakistan

Automation is priced per process, and a proposal covering an unspecified number of them is a rate card wearing a project title. Each process has its own systems, its own exceptions and its own approvals, and the second one is rarely cheaper than the first unless it touches the same systems.

Published rates give the reference. Junior work in this market is quoted at PKR 500 to 1,000 an hour, full stack development at PKR 3,500 to 8,000, with senior specialists at the top of that band. Where a piece of automation is scoped as a project, custom web application pricing at PKR 200,000 to 1,000,000 and upwards is the nearest published comparator, and it is honest because an automation is delivered as software with an owner, a log and an exception path.

Three things move a figure and none of them is the number of steps. Systems at the ends come first: two products with proper interfaces is one price, and a closed application where the only route in is the screen is another, with the fragility that comes with it. Approvals are second, because a process that pauses for a human decision needs a queue, a reminder, a delegation rule for leave, and an escalation nobody has thought about. Exceptions are third and they are where the effort actually sits, since the ninety percent that runs cleanly is straightforward and the awkward remainder decides whether anybody trusts the result.

Two costs continue after delivery. Tool subscriptions are one, if the automation runs on a commercial platform, and those are commonly billed in a foreign currency by task or by run, which for a Karachi business is an exchange rate exposure to note in the business case. Ownership is the other: somebody has to watch the failures, because an automation nobody monitors becomes a silent gap in a process rather than a saving. Everything above is market pricing. A real figure follows discovery, once the process is mapped and its volume is measured.

  • Each process priced individually, with the systems at both ends named in the estimate
  • Screen level automation against a closed application priced with its fragility
  • Approval queues, delegation during leave and escalation costed as part of the flow
  • Exception handling treated as the main line of work rather than as a remainder
  • Platform subscriptions and a named owner budgeted as continuing cost
02

How long a process automation takes to deliver

Reported timelines put a focused single scope go live at six to twelve weeks, and one process automated end to end fits comfortably inside that band. Three to six months applies once several processes, an approval hierarchy or integration across systems that do not want to cooperate are involved.

Mapping comes first and it is quicker than clients fear. Two or three sessions with the people who actually do the work, a stopwatch on the steps, and the volume pulled from a system rather than estimated in a meeting. What takes longer is the disagreement that mapping produces, because two branches doing the same process differently is common and somebody senior has to choose which version becomes the automated one.

Access is the second dependency and it follows the usual pattern. Service accounts, an interface or a licence to use one, a test environment holding realistic data, and permission from whoever owns each system. Where a step runs against a supplier's product, their support queue joins your plan.

Then a parallel run. We keep the manual process alongside the automated one for a defined period and compare the outputs line by line, because switching off the old way on a promise is how a business discovers a missed exception during a month end close. Two weeks is usually enough on a daily process and a full cycle is needed on a monthly one, which is a calendar problem rather than an effort problem and cannot be shortened by adding people. We then measure the before and after honestly, including the cases where the saving turned out smaller than the estimate.

  • Six to twelve weeks reported for one process automated end to end
  • Three to six months once several processes or an approval hierarchy are in scope
  • Volume and step times measured from systems rather than estimated in a workshop
  • A decision taken early where two branches run the same process differently
  • A parallel run before the manual process is switched off, with outputs compared
03

Deleting the step instead of automating it

Nearly every process we map contains work that exists because of something that stopped being true years ago. A report printed for a manager who retired. A second approval added after an incident in 2019, now applied to every transaction including the four hundred rupee ones. A spreadsheet maintained so one department can see what another department's system already shows. A form filled in by hand and then typed into the same system by the person who received it.

Automating those is worse than leaving them alone. You spend money, you make the unnecessary work faster and cheaper to keep, and you make it permanent, because an automated step has a script behind it and nobody removes a script that runs without error. The step is now defended by its own reliability. We have watched an organisation automate a reconciliation between two systems that should simply have been reading the same data, and the automation ran perfectly for two years while the underlying duplication got worse.

So the mapping session asks four questions of every step. Who reads the output of this, by name. What decision changes because of it. What would break if it stopped next Monday. And why does this data exist twice. The last one is the most productive question in the room, because the answer is usually that somebody could not get access to a system and built a copy instead, and restoring access deletes the step outright.

Thresholds are the other quick win and they need somebody with authority in the room, because nobody below that level will agree to remove a control. An approval applied to every purchase can usually apply above a figure instead, which removes most of the volume while leaving the control itself untouched. What we will not do is automate a process the owner cannot explain, because automation makes a process permanent and it deserves to be understood first. The honest version of the business case counts the hours actually returned rather than the hours theoretically touched, and we report it that way even when the number is smaller than everybody hoped.

  • Every step tested against who reads it, what decision it changes and what breaks without it
  • Duplicated data traced to the access problem that created it, then the copy retired
  • Approval thresholds raised where control is preserved and volume disappears
  • Automation declined on any process the owner cannot explain
  • Hours actually returned reported after the parallel run, including disappointing results
How we deliver

Delivering Process automation

One process, a cost in hours today, and a target that can be measured afterwards. These six steps add something the other practices do not need: an evaluation set built before anybody writes a prompt.

  1. 01

    Discover

    Volume, consistency, how an answer would be checked, and what a wrong one costs. We also give a capable person the same documents as a control, because if they cannot produce the answer, no model will.

  2. 02

    Blueprint

    A few hundred real cases with agreed correct answers, assembled with the people who do the work now. Where two experienced reviewers disagree, that is an undocumented rule, and it gets settled here.

  3. 03

    Build

    Extraction, validation against the purchase order or master record, confidence thresholds and the exception queue are built together. Retrieval is filtered by the asking user's existing permissions, never after the answer is generated.

  4. 04

    Test

    The evaluation set is run and scored against the human baseline, per document type, so you can see where accuracy holds and where it does not. Thresholds are set from that, not from a default.

  5. 05

    Go live

    Live on one process, with cost budgets and alerts already configured, exception owners named, and a written route back to the manual process that the people who would use it have rehearsed.

  6. 06

    Run

    Re-run the evaluation set on a schedule and after any model or prompt change, because a supplier redesigning an invoice can degrade accuracy quietly. Below the agreed threshold, the automation pauses.

Working together

The honest version of the business case

Automation business cases are often written as hours saved, and the hours are real, but they are only half the picture. An automation is a small system: it needs an owner, monitoring, a fallback and maintenance when the systems around it change. If the saving is a couple of hours a month, that overhead can exceed the benefit, and we will say so rather than build something that becomes a maintenance obligation nobody wanted.

The cases worth doing are high volume, repetitive, rule governed and stable. Approvals, matching, reconciliation, routine notification and data movement between systems all qualify. In those the saving compounds and the automation pays for its own upkeep. Before any of it, though, the process map usually finds steps worth deleting, and deletion has no running cost at all.

Credentials

Accreditations behind AI solutions

AI work reads from systems that already exist, so most of what follows is about the data platform underneath and the terms under which data moves.

Oracle

Partner

The data an assistant or forecast reads usually sits in Oracle. We build the extract views, document the schema, and use AI Vector Search in 23ai where retrieval belongs next to the data.

Microsoft

Partner

Azure hosts the processing where residency requires it, Power BI carries forecast output to the people who act on it, and SQL Server is often the source the model reads history from.

Google

Partner

Document AI handles the first pass on scanned and photographed invoices where layout varies, and Google Cloud gives a stated processing region when a document set cannot leave a jurisdiction.

FBR digital invoicing

Compliant integrations

Supplier invoices read automatically still have to reconcile to what was reported. Extracted sales tax values are checked against the purchase order and the return, with mismatches routed to a person.

HIPAA

Compliant practices

Clinical and claims documents are processed under a business associate agreement, with identifiers redacted where the task does not need them and provider terms that exclude training on your content.

Client words

What AI solutions clients say

Comments from people who run ai solutions systems day to day.

  • The handover was the part I judged them on. Configuration decisions documented with the reasoning, our administrators trained properly, and a checklist we actually worked through. We run it ourselves now, and calling them is a choice rather than a necessity.
    Head of Shared Services Multi site manufacturing group
  • What sold us was that they argued with our brief. We asked for a reporting layer and they came back saying the reporting was fine, the batch data underneath it was not, and fixing that first would cost less. That turned out to be right. Our first mock recall after go live took an afternoon instead of the better part of a week.
    Finance Director Food manufacturing group, Karachi
  • We had been through one failed implementation already, so we were sceptical of the whole category. The difference here was the migration work. Two full rehearsal loads before the real one, with a reconciliation pack we could check ourselves. Nobody had ever handed us evidence like that and asked us to sign it.
    Head of IT Wholesale distribution business
Questions

Questions about Process automation

It is priced per process, and any figure quoted before a process is mapped is a rate card in disguise. Published rates here put full stack development at PKR 3,500 to 8,000 an hour, and custom web application pricing of PKR 200,000 to 1,000,000 and upwards is the nearest project comparator. Systems at each end, approvals and exceptions move it far more than step count. We quote after mapping.

Reported timelines give six to twelve weeks for one process automated end to end, and three to six months once several processes or an approval hierarchy are involved. Mapping is quick. Getting service accounts and a realistic test environment takes longer, and the parallel run before the manual process is switched off is deliberately not rushed.

A rule does the same thing every time and can be read, tested and explained to an auditor. A model handles input that varies too much for rules, such as a document nobody standardised or free text a person wrote. We use rules wherever rules will do, because they are cheaper to run and far easier to defend, and reach for a model only where the rules genuinely run out.

If the automation is built on one, yes, usually billed per task or per run and often in a foreign currency, which is worth noting in a Pakistani business case. That can be entirely sensible for a small flow between two products. Where volume is high or the flow is unusual, code you own removes the subscription and takes on the plumbing instead. We will say which fits.

Then the options are an adapter against whatever the supplier does support, a scheduled file exchange, or driving the screen itself. Screen level automation works and it is fragile, because a supplier changing a field position breaks it silently. Where we use it, we monitor it as a business measure rather than a technical one, and we say plainly that it is a bridge rather than a destination.

It is handled the same way any integration is. Credentials in a managed store rather than in a script, transport encrypted, least privilege on every service account, and a log of what moved and when without recording the contents of sensitive fields. Where a step sends anything to a model provider, the region, retention and training exclusions are agreed in writing beforehand.

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