Artisans, within reach. Since 2003

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Artisans, within reach. Since 2003

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Retail

Retail Software Development

Retail tech built for store floors, field crews and peak season

Black Friday is the only real test most retail tech ever gets, and it happens on store floors, not in staging. In-store and field tools are what Kubikware builds for retailers, and every team we staff plans its releases around your busiest week.

Talk about your peak season

Where retail software gets stuck

01
Online and in-store data disagree.
Inventory, pricing and customer identity conflict across channels. A product shows in stock online and missing on the shelf, and every omnichannel promise needs an exception process.
02
Tools designed far from the floor.
Tools designed at head office and rolled out to stores get worked around by staff under time pressure. If the tool slows down a sale, it gets skipped, and the data goes with it.
03
Promotions that break pricing.
Prices and discounts that differ between channels turn every promotion into a support issue. Customers notice the difference before your team does.
04
Field teams stuck with calls and paper.
Crews on site lose time when apps and portals do not match how they actually work. Updates come by phone, photos get lost and the project office is always a day behind.
05
AI forecasts on data nobody trusts.
Demand and inventory predictions are only as good as the numbers underneath. When store teams do not trust the data, they ignore the forecast and order by instinct.

01
Online and in-store data disagree.
Inventory, pricing and customer identity conflict across channels. A product shows in stock online and missing on the shelf, and every omnichannel promise needs an exception process.
02
Tools designed far from the floor.
Tools designed at head office and rolled out to stores get worked around by staff under time pressure. If the tool slows down a sale, it gets skipped, and the data goes with it.
03
Promotions that break pricing.
Prices and discounts that differ between channels turn every promotion into a support issue. Customers notice the difference before your team does.
04
Field teams stuck with calls and paper.
Crews on site lose time when apps and portals do not match how they actually work. Updates come by phone, photos get lost and the project office is always a day behind.
05
AI forecasts on data nobody trusts.
Demand and inventory predictions are only as good as the numbers underneath. When store teams do not trust the data, they ignore the forecast and order by instinct.

01
Online and in-store data disagree.
Inventory, pricing and customer identity conflict across channels. A product shows in stock online and missing on the shelf, and every omnichannel promise needs an exception process.
02
Tools designed far from the floor.
Tools designed at head office and rolled out to stores get worked around by staff under time pressure. If the tool slows down a sale, it gets skipped, and the data goes with it.
03
Promotions that break pricing.
Prices and discounts that differ between channels turn every promotion into a support issue. Customers notice the difference before your team does.
04
Field teams stuck with calls and paper.
Crews on site lose time when apps and portals do not match how they actually work. Updates come by phone, photos get lost and the project office is always a day behind.
05
AI forecasts on data nobody trusts.
Demand and inventory predictions are only as good as the numbers underneath. When store teams do not trust the data, they ignore the forecast and order by instinct.

Where retail software gets stuck

01
Online and in-store data disagree.
Inventory, pricing and customer identity conflict across channels. A product shows in stock online and missing on the shelf, and every omnichannel promise needs an exception process.
02
Tools designed far from the floor.
Tools designed at head office and rolled out to stores get worked around by staff under time pressure. If the tool slows down a sale, it gets skipped, and the data goes with it.
03
Promotions that break pricing.
Prices and discounts that differ between channels turn every promotion into a support issue. Customers notice the difference before your team does.
04
Field teams stuck with calls and paper.
Crews on site lose time when apps and portals do not match how they actually work. Updates come by phone, photos get lost and the project office is always a day behind.
05
AI forecasts on data nobody trusts.
Demand and inventory predictions are only as good as the numbers underneath. When store teams do not trust the data, they ignore the forecast and order by instinct.

01
One inventory truth.
Every channel reads the same inventory number, from the website to the store floor. Promises made online match what the store can actually deliver.
02
Design with the floor, not for it.
The person using the tool is standing, interrupted and probably holding something. Designing with store staff, not just for them, is what gets the tool used during a busy shift.
03
Capacity planned for peak.
The architecture is sized for the busiest week of the year, not the average one. Load work happens before the season, so peak traffic is planned for instead of survived.
04
Forecasts built on one sales record.
One clean inventory and sales record comes first, then forecasting and automation on top of it. Stores get predictions they trust enough to actually order from.

01
One inventory truth.
Every channel reads the same inventory number, from the website to the store floor. Promises made online match what the store can actually deliver.
02
Design with the floor, not for it.
The person using the tool is standing, interrupted and probably holding something. Designing with store staff, not just for them, is what gets the tool used during a busy shift.
03
Capacity planned for peak.
The architecture is sized for the busiest week of the year, not the average one. Load work happens before the season, so peak traffic is planned for instead of survived.
04
Forecasts built on one sales record.
One clean inventory and sales record comes first, then forecasting and automation on top of it. Stores get predictions they trust enough to actually order from.

01
One inventory truth.
Every channel reads the same inventory number, from the website to the store floor. Promises made online match what the store can actually deliver.
02
Design with the floor, not for it.
The person using the tool is standing, interrupted and probably holding something. Designing with store staff, not just for them, is what gets the tool used during a busy shift.
03
Capacity planned for peak.
The architecture is sized for the busiest week of the year, not the average one. Load work happens before the season, so peak traffic is planned for instead of survived.
04
Forecasts built on one sales record.
One clean inventory and sales record comes first, then forecasting and automation on top of it. Stores get predictions they trust enough to actually order from.

What to look for in a retail software partner

What Kubikware provides

Whether you need a few senior people or a full pod, we put together the right mix of talent and plug it into the way your stores and field teams already work.

Tell us what you need

AI Transformation

Discovery sprint on your sales and inventory data, ending in a working prototype
AI for demand forecasting, inventory and store operations
Automation for field reporting and project tracking

Nearshore Staffing

Senior retail tech talent reporting to your technology leadership
Pods for MVPs and field app rebuilds
Recruiting for in-house retail technology roles

Product development

Product strategy and discovery for retail products
UX and UI for store staff, field crews and shoppers
Web, mobile and in-store builds, including checkout-free experiences
Field apps and project tracking portals
Maintenance through every peak season

Why Kubikware for retail software

Retail tech gets judged on its worst week, and that is the week we plan for.

Live apps for audiences that show up at once.

We built assigned seating with real-time seat locking for the AMC Theatres Android app, and helped HQ Trivia ship key features and live streaming.

Launch dates we hit.

AMC Theatres gave itself one year to bring assigned seating to Android. A tech lead and three senior engineers built it alongside AMC's team and launched on schedule.

AI audiences actually notice.

We build recommendations and personalization on structured engagement data, so they improve the experience instead of cluttering it. Audiences spend more time with content that fits them.

Senior people who skip the ramp-up.

Talent vetted to contribute in the first sprint, which matters when the date is already on the calendar. You spend your time on the launch, not on onboarding.

FAQ

Yes. We start with one reconciled record of sales and inventory, then prototype forecasting or store automation your teams can act on.

Retail tech teams use us for in-store technology, field apps, project portals and omnichannel tools, through staffing, product development or AI Transformation.

Yes. We have shipped a checkout-free MVP in three months, in front of key clients.

Yes. We design for people who are standing, busy and interrupted, from on-site crew apps to the portals that track every project.

Yes. The talent we put together works as part of your internal team and can report to your VP of Technology.

Peak season is coming either way

Tell us what has to hold up when it does.

Plan for peak

Retail Software Development

Retail Software Development

Retail Software Development

Retail Software Development

Retail tech built for store floors, field crews and peak season

Where retail software gets stuck

Where retail software gets stuck

Where retail software gets stuck

Online and in-store data disagree.

Tools designed far from the floor.

Promotions that break pricing.

Field teams stuck with calls and paper.

AI forecasts on data nobody trusts.

Online and in-store data disagree.

Tools designed far from the floor.

Promotions that break pricing.

Field teams stuck with calls and paper.

AI forecasts on data nobody trusts.

Online and in-store data disagree.

Tools designed far from the floor.

Promotions that break pricing.

Field teams stuck with calls and paper.

AI forecasts on data nobody trusts.

Where retail software gets stuck

Where retail software gets stuck

Online and in-store data disagree.

Tools designed far from the floor.

Promotions that break pricing.

Field teams stuck with calls and paper.

AI forecasts on data nobody trusts.

One inventory truth.

Design with the floor, not for it.

Capacity planned for peak.

Forecasts built on one sales record.

One inventory truth.

Design with the floor, not for it.

Capacity planned for peak.

Forecasts built on one sales record.

One inventory truth.

Design with the floor, not for it.

Capacity planned for peak.

Forecasts built on one sales record.

What to look for in a retail software partner

What to look for in a retail software partner

What to look for in a retail software partner

What to look for in a retail software partner

What Kubikware provides

What Kubikware provides

What Kubikware provides

What Kubikware provides

AI Transformation

Nearshore Staffing

Product development

Why Kubikware for retail software

Live apps for audiences that show up at once.

Launch dates we hit.

AI audiences actually notice.

Senior people who skip the ramp-up.

FAQ

FAQ

FAQ

Q/01Can you help us add AI to our retail operations?

Q/02What does Kubikware do for retail companies?

Q/03Can you build a retail MVP on a tight deadline?

Q/04Do you build apps for store staff and field crews?

Q/05Can your people report directly to our technology leadership?

Peak season is coming either way

Peak season is coming either way

Peak season is coming either way