Biometric Attendance System: A Complete Buyer's Guide 2026

Almost every biometric attendance evaluation runs the same way. Somebody collects quotes for three devices, compares the sensor specifications and the price, picks one, and installs it. Six months later the device works exactly as promised and the problem it was bought to solve is still there, because the problem was never at the door.

The device is the cheapest component of a biometric attendance system and the least consequential decision in the purchase. What matters is what happens to a punch in the two seconds after it is captured: whether it reaches a system that knows the employee's shift, applies the right overtime rule, survives an internet outage, produces a statutory register, and hands payroll a number it does not have to be re-keyed into. Buyers spend ninety per cent of the evaluation on the ten per cent of the cost that is the hardware.

This guide is organised around that. It covers what the three modalities actually do and who each of them fails, the hardware-versus-cloud decision that determines most of your five-year cost, what the whole thing comes to in rupees, what Indian law now requires, and how to run an evaluation that tests the parts that break.

One thing up front, because every recommendation below comes out of it. A biometric attendance system has two separate jobs, and vendors sell them as one. The first is identification: proving that the person punching is who they claim to be. That is the device's job, it is largely a solved problem, and the differences between reputable products are small. The second is computation: turning a stream of punches into hours, shifts, overtime, leave deductions and a payroll input that complies with the law. That is software, it is not solved, and the differences between products are enormous. If your current pain is buddy punching, you have an identification problem and the device matters. If your current pain is attendance disputes, wrong overtime, or three days of reconciliation before every payroll run, you have a computation problem and the device is irrelevant to it. Most buyers have the second problem and shop for the first.

What follows reflects the attendance deployments we run and migrate. Engage handles attendance for more than 40,000 employees across factories, retail chains, offices and field operations, which means most of the configurations described below are ones we have had to make work rather than ones we have read about. Where something below is flagged as a common failure, that is what we see in real deployments rather than a guess about what might be in them.

Prices in this guide are indicative Indian market ranges as at August 2026 and move with volume, model and region. Treat them as a sanity check on a quote rather than as a quotation. The legal position is general guidance for employers and is not legal advice.

What You Are Actually Buying

A biometric attendance system has four layers, and they are usually sold by different companies who each imply they are selling the whole thing.

Read the last column. The two layers that decide whether the system works are the two nobody demos, because a demo of an attendance engine is a screen of rules and a demo of a device is somebody putting their thumb on a scanner and a green light coming on.

A useful test at the start of any evaluation: ask the vendor to show you what happens when an employee works a night shift that crosses midnight, on the last day of the month, and takes half a day of leave in the same wage period. Every product handles a normal day. The differences are all in the awkward cases, and in Indian workplaces those are not edge cases, they are Tuesday.

The Three Modalities Compared

There are effectively three ways to capture attendance biometrically in 2026, and the choice is determined by your workforce rather than by your budget.

The market has moved decisively towards face over the last three years, driven by contactless preference after 2020, by throughput, and by device prices falling far enough that the premium over fingerprint no longer decides the question for most buyers.

That said, the modality choice is not one choice. Mixed is what we actually deploy for most employers with more than one kind of worker: fixed face devices at the main entrances where throughput matters, mobile face capture for field and multi-site staff, and a card or PIN fallback for the small number of people whom neither serves. Single-mode deployments are the exception rather than the rule, and they are usually a sign that one population was not considered at purchase.

Vendors dislike mixed configurations because they complicate the quote, and buyers dislike them because they look like three products instead of one. The thing to test in an evaluation is whether the attendance engine treats all three as the same punch, or whether mobile punches arrive as a separate stream that somebody has to merge every month. That distinction, rather than the hardware, is what makes a mixed setup either straightforward or permanently annoying.

Where Fingerprint Fails, and For Whom

Fingerprint attendance has a specific, well-documented failure mode, and the reason it deserves a section of its own is that it fails hardest for exactly the workforces most likely to be sold it on price.

Fingerprint matching depends on ridge detail on the surface of the finger. That detail is degraded by manual labour, by chemicals and solvents, by cement and abrasives, by prolonged wet work, and by age. Construction workers, machine operators, kitchen staff, cleaners, agricultural workers and warehouse pickers all show materially higher enrolment and match failure rates than office workers, and it is not marginal: in a factory population, the group who simply cannot enrol reliably is large enough that you must plan for them rather than treat them as exceptions.

The operational shape of the failure is worth understanding because it is not what buyers expect. A fingerprint device does not fail loudly. It fails by making people try three or four times, which at shift change turns into a queue, and a queue at shift change turns into two things: people clocking in after their shift started through no fault of their own, and a supervisor who starts waving people through and regularising it later. Once a supervisor is bulk-regularising attendance, you have lost the record you bought the system for, and you have added an audit problem you did not have before.

The sensor type matters more than the brand. Optical sensors, which are the cheap default, degrade badly with dirty, wet or worn fingers. Capacitive sensors handle those conditions considerably better and cost more. If you are buying fingerprint for a manual workforce and the quote does not say which sensor type it is, that is the first question, and a vendor who will not answer it plainly has told you something.

Three rules follow.

Never deploy fingerprint as the only method for a manual workforce. Face or card fallback is not a nice-to-have, it is the difference between a working system and a queue.

Test enrolment on your actual population before you buy, not on the office. Enrol thirty people from the shop floor, in their working state rather than freshly washed, and count how many enrol cleanly. That number decides the purchase and it takes an afternoon.

Treat exclusion as an accessibility question, not an inconvenience. An employee who cannot use the only means of marking attendance is being systematically marked late for a reason that has nothing to do with them, and if that correlates with a disability you have a problem well beyond attendance.

Face Recognition, Spoofing and Liveness

Face recognition is now the default for new deployments, and the useful questions about it are narrower than the marketing suggests.

Accuracy under good conditions is not a real differentiator any more. Reputable products all match reliably against an enrolled template in normal indoor lighting. The differences show up in three places: strong backlighting, which is what an entrance facing a doorway at 8am actually is; very high throughput, where the question is how many people per minute pass without stopping; and change over time, meaning whether the system still recognises someone after a beard, a haircut, glasses, a mask or two years.

The question that genuinely matters is liveness detection, and it is the one most quotes are silent about.

A face recognition device without liveness detection can be defeated by holding up a photograph. That is not a theoretical attack. It is the exact same buddy-punching problem the system was bought to eliminate, reintroduced in a form that is easier than the card-sharing it replaced, because a colleague's photo is on a phone already. Presentation attacks run from printed photos through video replayed on a screen to, at the sophisticated end, moulded masks, though for attendance fraud you only ever need the first two.

Liveness detection distinguishes a live face from a representation of one, using depth sensing, texture analysis, micro-movement, blink detection, or a combination. Implementations differ enormously in quality, and the trade-off is always between security and friction: aggressive liveness rejects genuine users on a bad day, weak liveness accepts a photo.

So ask three things, in these words.

Does the device perform liveness detection, and by what method? Depth or infrared based approaches are meaningfully harder to defeat than purely image-based ones. "Yes, AI-based" is not an answer.

Show me a photo attack, live, in the demo. Print a photograph of the person demonstrating, hold it to the camera, and watch. Any vendor confident in their liveness will do this without hesitation. A vendor who deflects has answered you.

What is the false rejection rate in poor light, and what is the fallback when it rejects? The fallback is the important half. A system that fails to a PIN entered by the employee is fine. A system that fails to a supervisor override is a buddy-punching mechanism with extra steps.

One more consideration specific to mobile face attendance, which section 9 returns to: on a phone you control neither the camera nor the environment, so liveness is doing more work and location verification carries part of the load that a fixed device gets for free.

Hardware or Cloud: The Decision That Costs Most

This is the architectural choice, it is made early, it is expensive to reverse, and it is usually made by default rather than by decision.

On-premise means devices connected to a server inside your network, running vendor software you licence, with your IT team responsible for the machine, the backups, the upgrades and the database. It was the standard model in India for two decades and a very large installed base still runs it.

Cloud means devices, or phones, pushing punches to a hosted platform you subscribe to, with no server of yours involved.

Cloud is the right answer for most Indian employers now, and there are two real exceptions rather than none: a single large manufacturing site with a capable IT function and no distributed workforce, where the on-premise economics are genuinely competitive; and organisations under a contractual or sectoral requirement to keep this data inside their own infrastructure, which is rarer than it is claimed to be but does exist.

The argument that decides it for multi-site employers is not cost. It is that on-premise deployments across sites drift. Each site's server ends up on a different software version with different shift masters and different holiday calendars, and a year later nobody can produce a consolidated attendance report without a manual merge. We migrate this situation regularly, and the recurring discovery is not that the old system was bad. It is that there were four of them and they disagreed.

The one technical requirement to insist on with cloud, and to test rather than take on trust, is offline buffering. An Indian site loses connectivity. The device must store punches locally and sync when the link returns, without losing anything and without duplicating anything. Ask how many punches the device buffers, and ask what happens when it fills. Then pull the network cable during the demo and watch.

What It Costs Over Five Years

Device price is the number every quote leads with and the smallest number in the exercise. Here is the whole picture, in indicative Indian market ranges as at August 2026.

Two observations about this table that change purchase decisions.

The AMC is the line that inverts comparisons. A device at ₹8,000 with a ₹6,000 annual maintenance contract costs ₹38,000 over five years. A device at ₹18,000 with a ₹2,000 AMC costs ₹28,000. The cheaper device is forty per cent more expensive, and this is not a hypothetical spread; it is inside the ranges above. Always ask for the five-year figure including AMC and always ask what happens to the AMC price in year three.

The largest cost is the one that never appears in any quote, which is the time your HR team spends every month reconciling attendance to payroll. If that currently takes two people three days a month, it is a substantial recurring cost, it is entirely a function of the software layer rather than the device, and it is the only line in the table a good system actually removes. This is why comparing devices on price is the wrong exercise: you are optimising a fifth of the cost and ignoring the half that a different choice would eliminate.

For a small office of twenty to thirty people, a single face device and a cloud subscription is a modest and predictable cost, and the wider tooling question for that size of team is in our guide for small businesses. For a manufacturing operation of five hundred across three sites, the device spend is real but it is still not what determines the five-year number. Model it properly before you take the cheaper quote.

Biometric Attendance and the Law in India

Two frameworks apply and they pull in different directions, which is why deployments configured for one usually breach the other.

Labour law requires you to keep the attendance record. Since the Labour Codes came into force on 21 November 2025, the muster roll and wage register obligations sit under the Code on Wages, and registers must be preserved for five years from the date of the last entry, up from three. The Factories Act, 1948 was repealed. The full position is in our guide to attendance compliance in India under the Labour Codes, and it is worth reading before you configure anything, because it determines what the system has to be able to produce.

Data protection law limits what you keep and for how long. Under the Digital Personal Data Protection Act, 2023 and the DPDP Rules notified in November 2025, biometric data is personal data. It requires notice, purpose limitation, security safeguards and erasure when the purpose ends.

A correction here, because it appears in most vendor material on this subject. The DPDP Act does not create a special sensitive personal data category, and biometric data has no separate legal status under it. That distinction existed under the SPDI Rules, 2011 and was deliberately not carried into the DPDP Act. Advice built on "biometrics are sensitive personal data requiring explicit consent" is describing a repealed framework. The actual obligations are the general ones, and employment is among the recognised legitimate uses, which makes processing attendance data for wage computation comfortable and makes reuse for anything else the problem.

The resolution of the apparent conflict between five-year retention and erasure-when-done is that they apply to different data, and this is the single most useful configuration decision in this article.

Most systems default to keeping all four indefinitely and almost nobody separates them. Ask the vendor how to configure template purge on exit. If the answer is that it is not configurable, you cannot comply without manual work forever.

Three further points that decide real deployments.

Aadhaar is not available to you for this. A private employer cannot compel Aadhaar-based biometric authentication for attendance. Aadhaar authentication by private entities is restricted following Puttaswamy and the subsequent amendments, and attendance is not a permitted purpose. Build your own enrolment. The temptation is real, because the Aadhaar number is already in your PF records, and it is the wrong shortcut.

Erasure has to reach the device. If templates live on the device as well as the server, removing an employee in the software does not remove them from the hardware. Device-level enrolment is a real store of personal data and it is routinely forgotten at offboarding.

The Supreme Court's November 2025 decision does not say what vendors say it says. A bench of Justices Pankaj Mithal and Prasanna B. Varale held that introducing a biometric attendance system in government offices was not invalid merely because employees had not been consulted first, allowing the Union's appeal against a 2014 Orissa High Court order. That is a decision about consultation in government service. It is not authority on private-sector data protection, and material citing it as settling that biometric attendance is legal for private employers is overreading it substantially.

Integration Is Where the Value Sits

Here is the test that separates a biometric attendance system from a biometric attendance device: what happens between the punch and the payslip.

In most Indian deployments the answer is a spreadsheet. Attendance software exports a file, somebody opens it, somebody adjusts it for the corrections that arrived after the export, somebody imports it into payroll, and somebody checks the result. That process runs every month, it takes days, it is where errors enter, and no biometric device improves it in any way. The device made identification more accurate and left the expensive part untouched.

What integration has to cover, in the order it bites:

Shift and roster awareness. A punch is meaningless without the shift it belongs to, and four shift patterns account for most of the defects we find in incumbent systems. Night shifts that cross midnight, where the system has to decide which calendar day the hours belong to. Break shifts, where a person works two separate blocks in a day and a naive system reads the gap as an exit and a fresh arrival. Open duration shifts, where there is no fixed window and hours have to be computed from the actual punches rather than measured against a schedule. This is the one that most often has no correct implementation at all, because the product assumes a shift master exists. And open location capture for field staff, where the punch is legitimate but the place is not a configured site, so it either fails or lands as an exception somebody clears manually.

All four are ordinary in Indian workplaces rather than edge cases, and a system that handles a fixed nine-to-six perfectly can fail every one of them. Test all four before you buy. If a vendor's demo only ever shows a standard day shift, you have not seen the product.

Leave and holiday. An absence has to resolve automatically against the leave balance, and holiday calendars vary by state and often by site, which is why we publish a current state-wise holiday list. If leave lives in a different system from attendance, somebody is reconciling two records of the same day every month. Our leave management and attendance run off one record for exactly this reason.

Overtime computation under the current rules. Overtime at twice the ordinary rate, triggered by eight hours in a day or forty-eight in a week, whichever comes first, with both tests applied independently, on the post-code wage definition, with the prescribed rounding. A system configured before November 2025 is very likely wrong on at least two of those, and the wage definition itself is worked through in our guide to employee salary structure in India.

Regularisation with an audit trail. Missed punches happen daily and legitimately. Every correction is an edit to a statutory record and needs to show who changed what, when, from what value, and who approved it. A system where a manager can silently overwrite a punch produces a register that evidences nothing.

Statutory register generation. The muster roll and wage register should come out of the system in the prescribed format for any named month, not be assembled from exports. Given that most states have not yet notified their final rules under the codes, the ability to regenerate a register in a new format later is worth more than being right about the format today.

Payroll, as a read rather than a transfer. If attendance and payroll are one system, the reconciliation problem does not exist, because there is nothing to reconcile. If they are two systems, insist on a real integration and budget for maintaining it, because the gap between them is where the errors in common payroll compliance mistakes tend to originate. The version of this failure that runs on spreadsheets is covered in replacing Excel with HR software.

Multi-Site, Field and Contract Workforces

Fixed biometric devices solve attendance for people who arrive at a building. A large share of Indian employment is not that, and this is where most buyers discover their system does not cover half their workforce.

Field staff. Sales, service, delivery, merchandising and installation teams have no premises to punch at. The workable answer is mobile face capture with location verification, which gives you both an identity and a place, and which, done properly, produces a stronger record than a fixed device does, because a fixed device proves only that someone's face was at that door. What does not work is a weekly self-declared timesheet approved in bulk, which is what most field operations run and which evidences nothing for compliance purposes. Our field tracking module exists for this record.

Multi-site operations. The requirement is one consolidated attendance record across sites, with site-level and role-level policy differences applied automatically. Retail chains and distributed manufacturing routinely have different shift patterns, different state holiday calendars and different Shops and Establishments rules per location. Handling that with one system per site does not scale; handling it with one policy for all sites is non-compliant. The system has to hold the differences as configuration.

Contract labour. The contract labour provisions moved into the OSH Code and the principal employer's exposure did not improve: if the contractor underpays, you pay. That makes the contractor's attendance record your evidence, and it sits inside the wider filing obligations on our compliance page. Biometric capture of contract workers at your gate, held against the contractor's own muster roll, is the practical control, and the mismatch between the two is the thing worth looking at monthly. It is also the place where fingerprint modality choice matters most, because contract labour in construction and manufacturing is the population fingerprint serves worst.

Hybrid office staff. The genuinely unsettled category. Biometric attendance for a hybrid knowledge worker mostly measures building occupancy rather than work, and deploying it for that purpose tends to cost more in trust than it returns in data. If the aim is occupancy planning, say so and measure it as occupancy. If the aim is wage computation for people whose pay does not vary with hours, ask what the record is actually for before you buy it. The distributed-team version of this question is worked through in our guide to cloud-based attendance software for distributed teams.

How to Evaluate a Biometric Attendance System

Most evaluations compare specifications. Specifications are the part vendors control. Run these seven tests instead, in this order, and the shortlist resolves itself.

1. Enrol thirty of your actual workers. Not the office, and not freshly washed. The shop floor, mid-shift. Count clean enrolments. This one test eliminates the wrong modality before you have spent anything, and it is the test almost nobody runs.

2. Attack the liveness. Print a photo of the person demonstrating and hold it up. Play a video of them on a phone. If the device accepts either, it does not solve buddy punching, which is probably why you are buying it.

3. Pull the network cable. Punch ten times offline. Reconnect. Confirm all ten arrived, once each, with correct timestamps. Offline buffering is claimed universally and implemented variably.

4. Run the four shift patterns. A night shift starting 10pm and ending 6am across a month boundary. A break shift with two blocks in one day. An open duration shift with no fixed window. And a field punch from a location that is not a configured site. Ask to see the resulting hours, overtime and payroll input for each. These four find more defects than the rest of the evaluation combined, and the open duration case is the one most likely to have no correct answer at all.

5. Ask for a muster roll for a named month. In the prescribed format, every person, every day, with marks for absence and weekly off. If it comes out as a raw punch export, the product is a data collector and you will be building the register yourself.

6. Ask how to purge biometric templates on exit while retaining attendance records for five years. If it is not configurable, you have a permanent manual compliance task.

7. Ask for the five-year cost including AMC, and what the AMC costs in year three. Get it in writing. This is where the cheap quote usually stops being cheap.

If attendance is one line in a wider system selection, our HR software buyer's guide covers the rest of that evaluation. Then two questions for the reference customer rather than the vendor, which are worth more than the whole demo: how many days does your payroll reconciliation take now compared with before, and how many attendance disputes do you get a month. Those are the two numbers the system exists to move, and running the function on numbers rather than impressions is the subject of our piece on data-driven HR.

Questions People Ask

What is a biometric attendance system?

A biometric attendance system records employee attendance by identifying people through a physical characteristic, most commonly a fingerprint or face, rather than through a card, PIN or signature. It has four parts: a capture device that reads the characteristic, a store holding the enrolled template, an attendance engine that converts punches into hours by applying shift, break, overtime and leave rules, and an integration that feeds the result into payroll and statutory registers. The device is typically ten to twenty per cent of the five-year cost; the attendance engine and integration are most of the rest and most of the value.

Which is better for attendance, fingerprint or face recognition?

Face recognition is the better default in 2026 for most workplaces, because it is contactless, faster at high throughput, and does not fail for workers whose fingerprints are worn by manual work. Fingerprint remains reasonable and cheaper for clean office environments, small teams and low-throughput doors, and the sensor type matters more than the brand: capacitive sensors handle wet, dirty and worn fingers considerably better than the optical sensors used in budget devices. For factories, construction, warehousing or any workforce doing manual work, fingerprint should not be the only method offered.

How much does a biometric attendance system cost in India?

Indicatively, as at August 2026: fingerprint devices ₹3,000 to ₹12,000 each, face recognition devices ₹8,000 to ₹35,000 each, installation and power backup ₹1,500 to ₹6,000 per device in year one, and an annual maintenance contract of ₹1,500 to ₹10,000 per device per year from year two. Software is charged per employee per month for cloud products or as a licence plus support for on-premise. Over five years the AMC and the software subscription usually exceed the device cost several times over, so a device-price comparison can easily point at the more expensive system. Ask for a five-year total including AMC.

Is biometric attendance legal in India?

Yes, subject to conditions. Fingerprint and face templates are personal data under the Digital Personal Data Protection Act, 2023, so employees must be given notice of what is collected and why, the data may only be used for the purpose stated, it must be secured, and it must be erased when that purpose ends. Employment is among the recognised legitimate uses, which covers attendance data used to compute wages. A private employer cannot compel Aadhaar-based biometric authentication for attendance, as Aadhaar authentication by private entities is restricted and attendance is not a permitted purpose. The Supreme Court's November 2025 decision concerned consultation with government employees before introducing such a system and does not settle the private-sector position.

How long should biometric attendance data be retained?

Split the data, because two different rules apply. Attendance records, meaning who worked which hours on which day, must be preserved for five years from the date of the last entry under the Code on Wages (Central) Rules, 2026, and the statutory obligation is the basis for holding them. Biometric templates serve only to identify the person at the moment of the punch and should be purged when the employee leaves. Raw biometric images should not be stored at all. Most systems default to retaining everything indefinitely, which fails the storage limitation principle, and almost none separate the two by default.

Can a biometric attendance system be fooled by a photo?

A face recognition device without liveness detection can be, which reintroduces the buddy punching the system was bought to prevent. Liveness detection distinguishes a live face from a photograph or a video replay using depth sensing, infrared, texture analysis or micro-movement, and implementation quality varies widely between products. Ask which method a device uses, and test it during the demo by holding a printed photograph of the person demonstrating up to the camera. Also ask what the fallback is when liveness rejects a genuine user: a PIN entered by the employee is acceptable, a supervisor override is a buddy-punching route with extra steps.

Should we choose a cloud or on-premise biometric attendance system?

Cloud suits most employers now, and especially anyone with more than one site or any field or remote staff, because every location writes to one consolidated record and upgrades are continuous rather than deferred projects. On-premise remains defensible for a single large site with a capable IT function and no distributed workforce, or where a contractual requirement demands the data stay in your own infrastructure. The failure mode of multi-site on-premise deployments is drift: each site's server ends up on a different version with different shift and holiday masters, and consolidated reporting becomes a manual merge. With cloud, insist on testing offline buffering, since Indian sites lose connectivity and the device must hold punches locally and sync without loss or duplication.

Does a biometric attendance system work for field employees?

Not a fixed one, since there is no door to arrive at. Mobile face capture with location verification is the workable approach: it produces both an identity and a place, and it can evidence hours in a way a self-declared weekly timesheet cannot. The requirements are liveness detection that works on an uncontrolled camera, offline capture that syncs when the phone regains signal, and location data retained only as long as the attendance record it supports rather than as a continuous track. The best configuration for most employers with mixed workforces is fixed devices at main sites plus mobile capture for field staff, with both arriving in the same attendance record rather than as separate streams somebody merges.

What is the difference between a biometric attendance system and attendance software?

The biometric system is the identification layer: it establishes who is punching. Attendance software is the computation layer: it turns punches into hours by applying shifts, grace periods, breaks, weekly offs, holidays, leave and overtime rules, and produces the payroll input and statutory registers. A biometric device without capable attendance software gives you accurate data about a problem you still have to solve by hand. Attendance software without biometrics still computes correctly but cannot prevent buddy punching. Most buyers who describe their problem as attendance disputes, wrong overtime or slow payroll reconciliation have a software problem and are shopping for hardware.

Where This Leaves You

Decide the modality from your workforce rather than your budget: face for manual and high-throughput environments, fingerprint only where the population and the conditions actually support it, mobile capture for anyone without a fixed site, and a fallback for everyone the primary method excludes. Decide the architecture from your geography: cloud unless you are a single site with real IT capability. Then spend the rest of the evaluation on the attendance engine and the payroll integration, because that is where both the cost and the benefit actually are.

So run it in this order. Start with the thirty-person enrolment test before you shortlist, because it can eliminate an entire modality in an afternoon. Attack the liveness in the demo. Pull the cable. Run all four awkward shift patterns (night, break, open duration and an off-site field punch) through the whole chain to a payroll figure. Ask for a muster roll in the prescribed format. Ask for the five-year cost including year-three AMC in writing. Then check the template purge configuration, because that is the compliance item you will otherwise be doing by hand forever.

What you should not do is buy a device and treat the software as something to sort out afterwards. That is the sequence most Indian employers follow, it is why so many are running accurate identification on top of a manual reconciliation, and it is the reason the second purchase in this category usually happens three years after the first.

The compliance requirements that decide what your system must produce are in our guide to attendance compliance in India under the Labour Codes. The architecture question in more depth, for distributed and multi-site teams, is in cloud-based attendance software for distributed teams. The wider statutory picture is in our labour law compliance checklist.

If you would rather the punch, the shift rules, the overtime computation, the leave balance and the payslip all came out of one record instead of four systems that have to agree, that is what our attendance management software is built to do. Book a free demo and bring your hardest shift pattern rather than your simplest. It is a much more useful test than a feature list.