ValtixCube
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What we have built, by industry

Case studies from the industries we work in, followed by two automation projects: an AI tool that finds the cheapest vendor for each product, and an agent that keeps an eye on stock. Each covers the problem, what we built and what changed. Client names are not shown.

Case studies by industry

A recruiter reviewing a grid of candidate profile photos

What did we build for HR teams?

For hiring teams slowed down by manual screening, we built AI-powered recruitment and screening platforms with resume parsing, candidate shortlisting, automated follow-ups and recruiter dashboards. The result was less manual screening, shorter hiring cycles, and a better experience for recruiters and candidates.

The problem

Slow recruitment cycles, heavy manual screening, an inconsistent candidate experience and little visibility into how hiring was performing.

What we built

  • AI-powered recruitment and screening platforms
  • Resume parsing and candidate shortlisting
  • Automated communication and follow-up workflows
  • Hiring dashboards and recruiter productivity tools

What changed

  • Less manual screening effort
  • Faster hiring cycles
  • Better recruiter efficiency and candidate experience
A warehouse team checking stock on a tablet beside packed boxes

What did we build for retail and ERP?

For retail and distribution businesses running disconnected inventory tools, we built unified ERP and inventory platforms, agent sales and commission systems, order tracking dashboards and mobile apps for field teams. Operations moved under one system, stock became visible, and manual errors dropped.

The problem

Disconnected inventory systems, manual reconciliation, low visibility of sales and slow workflows for sales agents.

What we built

  • Unified ERP and inventory management platforms
  • Agent-based sales and commission management systems
  • Order lifecycle tracking and reporting dashboards
  • Mobile-first apps for retail and field teams

What changed

  • Operations controlled from one system
  • Clearer stock visibility for better decisions
  • Fewer manual errors and less operational overhead
A shopper paying with a phone QR code next to an online store on a laptop

What did we build for e-commerce?

For growing online businesses facing integration and scaling problems, we built end-to-end e-commerce and marketplace platforms with customer, admin, delivery and partner apps, connected to payments, logistics and POS. Operations scaled, partner integrations went live faster, and more orders completed successfully.

The problem

Integration complexity, operational bottlenecks and scaling problems that started to hurt the customer experience as the business grew.

What we built

  • End-to-end e-commerce and marketplace platforms
  • Multi-app ecosystems for customers, admins, delivery and partners
  • Integrations with payment, logistics and POS systems
  • Partner onboarding and channel management tools

What changed

  • E-commerce operations that scale with demand
  • Faster partner integrations and go-lives
  • Higher order success rates and better operational control
Clinicians reviewing medical scans on a monitor in a hospital office

What did we build for healthcare?

For healthcare products that needed high reliability, secure data handling, offline-first workflows and device integration, we built AI-enabled diagnostic apps, sensor-connected platforms, medical kiosks and secure backends. Clinical workflows improved, device data synced reliably to the cloud, and medical data stayed protected.

The problem

High reliability requirements, secure handling of medical data, offline-first workflows and integration with medical devices.

What we built

  • AI-enabled diagnostic and medical applications
  • Smart device and sensor-integrated platforms
  • Medical kiosks and self-assessment systems
  • Secure backend systems and data pipelines

What changed

  • Improved diagnostic and clinical workflows
  • Reliable device-to-cloud data synchronization
  • Secure, compliant handling of medical data
A team in a meeting room looking at a 3D city model on a large screen

What did we build for real estate?

For property businesses relying on spreadsheets and disconnected tools, we built inventory and availability systems, sales and leasing workflows, lead tracking and booking tools, and revenue and occupancy dashboards. Inventory came under control, lead-to-conversion became visible, and manual work went down.

The problem

Manual processes, spreadsheets and disconnected tools, which left teams with little visibility and weak tracking of how leads converted.

What we built

  • Property inventory and availability management systems
  • Sales and leasing workflow platforms
  • Lead tracking, booking and documentation tools
  • Revenue, occupancy and performance dashboards

What changed

  • Better control of inventory and availability
  • Clearer view from lead to conversion
  • Less manual operational work

What have we automated with AI?

Two projects where software now does work people used to do by hand: an AI tool that compares what several vendors charge for the same product and points to the cheapest, and an agent that checks stock across web portals on a schedule. Both run inside the team's daily work.

Two colleagues comparing figures on a computer screen in an office
ExampleOne product, five vendors
  1. Vendor A₹2,499
  2. Vendor B₹2,390
  3. Vendor C₹2,640
  4. Vendor D₹2,149Cheapest
  5. Vendor E₹2,390

Buying from Vendor D saves ₹491 on this item against the highest price.

How does our tool find the cheapest vendor?

The same product is often sold by several vendors at different prices, and the gap can be large. We built an AI tool that collects the price of each product from multiple vendors, matches listings that refer to the same item, and points to the cheapest option. Buyers stop overpaying, and every purchase starts from the lowest price on offer.

The problem

Buyers opened one vendor after another and copied prices into spreadsheets by hand. It was slow, easy to get wrong, and the cheapest offer was often missed.

What we built

  • Price collection for each product from multiple vendors
  • AI matching, so the same product is compared even when vendors name it differently
  • A side by side view with the cheapest vendor highlighted
  • Separate workspaces and permissions for each team

What changed

  • Purchases start from the lowest available price, which saves cost
  • No more manual price checks across vendor sites
  • One place to see every vendor's price for a product
A professional working with floating charts and data panels

How does our agent keep an eye on stock?

For businesses that had to check stock levels across several online portals by hand, we built an AI agent that does the checking for them. It visits each portal on a schedule, reads the current stock, keeps a history for every business separately, and shows each team what changed since the last check.

The problem

Stock information sat in several web portals with no simple export, so staff checked them one by one and changes were often noticed too late.

What we built

  • An AI agent that checks each portal on a schedule, with no one at the keyboard
  • A separate, private space for every business that uses it
  • A stock history, so changes can be tracked over time
  • A simple way for dashboards and other systems to read the results

What changed

  • No more manual portal checks to know current stock
  • Stock changes are picked up on time instead of when someone remembers
  • One agent serves several businesses without mixing their data

Have a problem like one of these?

Send a short note about the problem, the users and any deadline. We will reply with questions or a time to talk.

+91 9790817594 contact@valtixcube.com
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