AI & Software Development
Case Studies
Real engagements, real constraints, measurable outcomes. AI work comes first: agents, copilots and automation running in production. Then the web, mobile and enterprise products we've built and rebuilt.
- 50% fewer support tickets
- 95% AI flagging accuracy
- 24x7 multilingual AI agent
AI That Works With Real Users
AI features that had to hold up in production, not just in a demo: validated outputs, measured accuracy and the client's team in control.
AI Case StudyReal Estate PropTech
PropTech Revenue Intelligence Platform
0 → fully shipped SaaS: 6 modules, 60+ features, 500,000+ records synced
Built a multi-integration PropTech SaaS from zero, with a 24x7 multilingual prospect AI agent and a sync layer that unifies AppFolio, Rent Manager and Rentvine data and catches its own failures.
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AI Case StudyMarketplace
AI-Powered Event Marketplace
Structured AI output enforced: no malformed responses reaching the frontend
An all-in-one event marketplace connecting vendors, planners and customers, where AI search and a vendor copilot had to work reliably in production, not just in demos.
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AI Case StudyEnterprise
Teams Call Quality AI Analyzer
50% fewer support tickets, with 95% AI flagging accuracy
Every Microsoft Teams call quality complaint meant a support ticket and a manual investigation call. We built an AI monitoring layer that flags real issues before they become tickets.
Read case studySoftware That Lasts
Web, mobile and enterprise builds delivered under real constraints: fixed launch dates, payment flows, legacy code and data that can't be wrong.
Indian Grocery Ecommerce Platform
$5,000+/month in lost revenue recovered, 98.27% crash-free
A US online grocery platform for the Indian diaspora had a webview app with no crash visibility and a silent billing flaw. We rebuilt the foundation and shipped native apps on top of it.
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Enterprise Appraisal Management System
Delivered production-ready in 2 months for 500+ workers, then awarded a second project
A multinational agribusiness needed its tea estate and factory worker appraisals off paper and spreadsheets, live before a fixed appraisal cycle just two months away.
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B2B Credit Card Payment Platform
0 → fully shipped app, backend and admin panel, with gateway and OTP fallback
An early-stage FinTech startup wanted businesses to pay rent, GST and vendors by credit card. We built the full platform, and proposed the architecture that made it production-safe.
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Unified Infrastructure Monitoring Dashboard
One live view across all regions, and 40% lower storage costs
An enterprise's IT teams watched FreshService, Zscaler and other tools separately, so outages slipped through. We built one real-time dashboard for the head office, and caught a hidden cost problem along the way.
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Faculty Recruitment Management System
75% less screening time, validated at 10,000+ concurrent users
One of India's most prestigious arts and science colleges screened 800+ faculty applications by hand. We digitized the entire hiring lifecycle and load-tested it to 10,000+ concurrent users.
Read case studyQuestions About Our Work
What buyers usually ask after reading our case studies. If yours isn't here, reach out. We respond to every message personally.
Contact us for moreOur AI work in production includes AI search and a vendor copilot for an event marketplace, an AI layer that flags Microsoft Teams call quality issues before they become support tickets, and a 24x7 multilingual prospect AI agent for a PropTech platform. Each one runs for real users, not as a demo.
The Teams call quality analyzer cut support tickets by 50% with 95% AI flagging accuracy. On the event marketplace, structured output validation means no malformed AI responses reach the frontend. The PropTech agent answers prospect questions, checks availability and schedules tours across text, email, chat and phone around the clock.
We treat AI like any other production system. Outputs are validated against a defined structure before they reach users, features are tested against real cases, and quality, latency and cost are monitored after launch. Where it matters, the client's team stays in control of what the AI does.
No. AI leads our work, but most of our case studies are web, mobile and enterprise builds: payments, ecommerce, internal tools and data-heavy SaaS. Most AI features need a solid product around them, and one team building both avoids hand-off gaps.
No. We don't train models on client data, and we can deploy AI features in your own cloud so the data stays inside your environment.
Most AI engagements start with a two-week AI Discovery Sprint: a use-case audit, a working prototype of the strongest idea, and a clear go or no-go before you commit to a full build. You can also book a free discovery call first.
Have a project like these?
Book a free 30-minute discovery call. Tell us what you're building and we'll tell you how we'd approach it, including whether AI is the right answer at all.