AI-NATIVE ENGINEERING

AI That Works. Software That Lasts.

Anyone can demo AI. We put it into production. Xlorit builds AI agents, RAG systems and intelligent automations, plus the web and mobile platforms they run on. And because we engineer with AI at every step, you ship faster without giving up reliability.

  • AI Agents
  • Multi-Agent Systems
  • RAG
  • AI Copilots
  • Automations
Platform dashboard overview
Analytics dashboard view
Workflow dashboard view
Platform dashboard overview
Analytics dashboard view
Workflow dashboard view

10K+

Active Daily Users

40%+

Efficiency Gains

95%

AI Flagging Accuracy

7+

Years Building Software

The technology behind AI that works

We work across leading AI models, agent frameworks and vector databases, and the cloud, web and mobile stack that runs them in production. Model-agnostic, so you're never locked to a single provider.

  • OpenAI
  • Claude
  • Gemini
  • Llama
  • Qwen
  • Hugging Face
  • Ollama
  • LangChain
  • LangGraph
  • AutoGen
  • Nomic
  • Qdrant
  • Chroma
  • Next.js
  • React
  • Node.js
  • Django
  • Flutter
  • AWS
  • Azure
  • DynamoDB
  • Redis
  • Firebase
  • GitHub Actions

Our Process

Contact Us

We keep things simple and structured so you always know what's happening next. Clear steps, steady progress, and no unnecessary complexity.

01

Discovery Call

We begin by understanding your technical constraints, team structure, and business objectives, including where AI will genuinely help and where it won't. This shapes every architectural decision that follows.

02

Technical Build

Architecture is documented, approved, and built in AI-assisted sprints. AI features are evaluated against real cases before release, and milestones are tied to measurable engineering outcomes.

03

Build & Scale

Systems are load-tested, hardened, and handed over with full observability, including AI output quality and cost monitoring. We remain available for long-term engineering support.

Case Study Teasers

We take a structured approach to improving real products. Every decision is made with performance and long-term growth in mind.

PropTech Revenue Intelligence Platform
Real Estate PropTech

PropTech Revenue Intelligence Platform

DjangoReactAzureAppFolio
Outcome

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.

AI-Powered Event Marketplace
Marketplace

AI-Powered Event Marketplace

Next.jsAI SearchAI CopilotRedis
Outcome

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.

Teams Call Quality AI Analyzer
Enterprise

Teams Call Quality AI Analyzer

GPTMicrosoft TeamsAWS LambdaCloudWatch
Outcome

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.

Indian Grocery Ecommerce Platform
Ecommerce

Indian Grocery Ecommerce Platform

FlutterNext.jsAzureAuthorize.net
Outcome

$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.

Enterprise Appraisal Management System
Enterprise

Enterprise Appraisal Management System

Node.jsAWS LambdaAWS AmplifyAzure AD
Outcome

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.

B2B Credit Card Payment Platform
FinTech

B2B Credit Card Payment Platform

FlutterDjangoReactKYC
Outcome

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.

Unified Infrastructure Monitoring Dashboard
Enterprise

Unified Infrastructure Monitoring Dashboard

AWS LambdaDynamoDBFreshServiceZscaler
Outcome

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.

Faculty Recruitment Management System
Education

Faculty Recruitment Management System

DjangoReactCeleryRedis
Outcome

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.

Our Services

Strategic Engineering Services

AI Development

AI agents, RAG systems, copilots and automations that work in production, built with the output validation, evaluations and monitoring that keep them reliable.

Web Development

From backend architecture to frontend delivery, we build web applications engineered to handle real traffic and scale without rework.

Mobile Application Development

We build cross-platform mobile apps with Flutter, tested under real network conditions and device fragmentation before they ever reach a client demo.

UI/UX Design

We design interfaces around how people actually use the product, not as a decorative layer added at the end.

AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.AI that works. Built for scale. Engineered for clarity.
IS THIS FOR YOU?

Who This Is For

Our services are built for teams that need more than code: AI that holds up with real users, and an engineering partner who understands what it takes to scale.

01
AI Reliability

Teams With Stalled AI Pilots

You have an AI demo that impressed the room. Now it needs to work reliably for real users, at real volume, at a cost that makes sense.

02
Automation

Teams Stuck in Manual Workflows

Your team spends real hours on repetitive work, such as support triage, status reporting or data reconciliation, that the right AI integration could handle.

03
Growth Stage

Post-MVP & Growing SaaS

You've validated the product and now need a platform that scales, plus AI features your users will actually use, without piling up tech debt.

04
Modernisation

Enterprise Teams

Internal teams with legacy constraints looking for an engineering partner who can modernise infrastructure without disrupting live operations or existing revenue.

XLORITEngineers

Senior engineers at the core, AI agents in the loop. Select a standard to see where it fits.

How We Engineer

These aren't slogans. They're the standards every engagement is held to, from a two-week build to a multi-year retainer.

Every engagement starts with a documented system architecture review. We don't write a line of code until we understand the constraints, failure modes, and growth trajectory of your platform.

We design for growth that hasn't happened yet, not just the traffic you have today. One client engagement has run for over two years without a rebuild, because the original architecture was built to absorb growth instead of resisting it.

We use AI across planning, coding, review and testing, with senior engineers owning every decision. You get faster delivery without trading off code quality or reliability.

Most of our engagements don't end at launch. Several of our enterprise clients have kept us on for ongoing support over multiple years, including one relationship now in its fourth year of continuous use.

We hold AI to the same standard as the rest of the system. Outputs are validated before they reach users, features are evaluated against real cases, and quality and cost are monitored after launch, so the AI behaves the same on every request.

Structured Engineering

An appraisal management system delivered 97% bug-free under an urgent two-month deadline, the clearest proof of our process discipline.

View Case Study

Advanced Architecture

A B2B credit card payment platform with four payment gateways and SMS verification coordinated into one distributed system.

View Case Study

Reliable Performance

An AI-assisted recruitment and admissions platform serving 10,000+ concurrent users, still running reliably in its fourth year.

View Case Study

Testimonials

What it's like to work with us, shared by the teams we've partnered with.

Real Estate PropTech SaaS

We came to XLORIT through a referral, and a year later they're still the team we trust with our core data. The architecture has held up as we've added more platforms and more properties, which is exactly what we were worried about at the start.

PT

PropTech SaaS client

Referral engagement, United States

Case study →
Event marketplace

We were an early-stage startup with a big idea and not much room for mistakes. The team took us from nothing to a live marketplace with AI search and a vendor copilot, and they were honest with us the whole way about what would and wouldn't work.

MC

Marketplace client

Early-stage startup

Case study →
Enterprise client

Earlier, every call quality complaint meant a ticket and then a phone call just to find out what happened. Now issues get flagged automatically, and most of the time we know before the user even calls us. Our ticket volume dropped by half.

EC

Enterprise client stakeholder

IT team

Case study →
Indian Grocery Ecommerce Platform

Two and a half years in, they feel less like a vendor and more like our own tech team. If something breaks at night here in the US, it's usually fixed by the time I wake up. I can't say that about anyone else we've worked with.

EC

Ecommerce client

US grocery platform

Case study →
Multinational agribusiness

We had a fixed appraisal cycle and only two months to get ready. XLORIT understood the urgency from day one, made the hard scoping calls early, and delivered on time. The system works very well, and our people across the estates are actually using it.

EC

Enterprise client stakeholder

Multinational agribusiness

Case study →
B2B payment platform

As an early-stage startup, we needed a team that thinks like a co-founder on the tech side, not just people who write code. That's exactly what we got.

FT

FinTech client

Early-stage FinTech startup

Case study →
Enterprise client

Finally, one screen for every region. When something critical happens we see it in real time, not the next morning in a report. It's become the first thing the team looks at every day.

EC

Enterprise client stakeholder

IT team

Case study →
Client institution

We processed more than 800 applications this cycle without the usual chaos. Everything from application to final selection is in one place, and the reports are exactly what management keeps asking us for.

HR

HR Lead

Client institution

Case study →

Have Questions?

We keep our process transparent and our answers direct. If your question isn't here, reach out — we respond to every message personally.

Contact us for more

We begin with a discovery call to understand your technical landscape, then produce a scoped architecture proposal. Once approved, we work in two-week sprints with weekly engineering syncs and continuous documentation.

It depends on scope. Fixed-scope projects have ranged from a few weeks to four months, depending on complexity. Staffing and retainer engagements are ongoing, with several of ours running one to two years or more.

We've worked with early-stage startups, enterprise teams, and established institutions across fintech, ecommerce, real estate, and education. Our clients range from enterprise product teams to single-founder SaaS products.

We're model-agnostic. We choose the model for each task based on accuracy, speed, cost and data requirements, and design the system so models can be swapped as better options appear, without a rebuild.

Your data stays yours. We use providers and configurations that don't train on your data, apply access controls so AI only sees what it should, and can deploy within your own cloud when compliance requires it.

Yes. Most stalled AI projects fail on reliability, not the model: inconsistent outputs, no evaluation, rising costs. We audit what exists, add the validation and monitoring it's missing, and get it production-ready.

Start with an AI Discovery Sprint. In two weeks we assess your use cases, build a working prototype for the most promising one, and give you a clear go or no-go before you commit to a full build.

Yes, always. All engagements are covered by a mutual NDA before any technical discovery begins. We treat client IP and system details with the same discipline we apply to engineering.

Get Started

Ready To Put
AI To Work?

Let's talk about your platform, where AI can make a real difference, and how we can help you scale with confidence.

Let's Talk About Your Project

Build With Clarity,
Not Guesswork

Tell us about your platform and your constraints. We'll tell you exactly what it would take to get it right.

  • Expect a response within 24 hours
  • Happy to sign an NDA if needed
  • Get practical input from engineers who've shipped production systems
Mohammed Ibrahim — Founder & CEO

Mohammed Ibrahim

Founder & CEO

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