Your App With
AI That Actually
Does Something.
AI features that impress in a demo but don't deliver value in daily use are not worth building. At Burraq, we integrate AI capabilities that solve real problems for your users — smarter search, personalised recommendations, automated classification, and intelligent automation — built on proven models, not experimental ones.
Practical AI, Not Demo AI
We evaluate every AI integration against one question: does this make the app genuinely more useful for the user? If the answer is no, we say so. If yes, we build it on the right model with the right architecture.
OpenAI
& Leading Models
Real
User Value
100%
Documented Integration
What You Get
What's Inside Every Project
Personalised Recommendations
Recommendation engines that suggest relevant products, content, or actions based on individual user behaviour — the feature that keeps users in the app and drives repeat engagement.
NLP & In-App Chatbots
Natural language processing for search, support chatbots, and conversational interfaces — powered by GPT-4 or fine-tuned models where generic responses aren't sufficient.
Image & Object Recognition
Camera-based features — product scanning, document capture, face detection, and visual search — integrated via Google Vision, AWS Rekognition, or custom models.
Predictive Analytics
Churn prediction, demand forecasting, and anomaly detection — AI that gives your team early warning signals before problems become visible in conventional dashboards.
Smart Search
Semantic search that understands intent — not just keyword matching. Users find what they're looking for even when they don't use the exact right words.
OpenAI & Model Integration
GPT-4, Gemini, Claude, and other leading models integrated via API — rate-limited, cost-managed, and monitored so AI features remain performant as usage scales.
Our Approach
AI Is A Tool. The Question Is Whether It Solves The Right Problem.
We don't add AI to apps because it looks impressive in a pitch deck. We add it when it makes the app genuinely more useful. Every AI feature we build starts with a clear user problem and a measurable outcome — not a technology looking for a use case.
AI feature scoped around a real user problem — not a technology showcase
Model selected based on accuracy, cost, and latency requirements
Fallback behaviour designed for when AI confidence is low
Cost per API call estimated and monitored — no surprise infrastructure bills
Our Process
How It Works
Feature Scoping
We define the exact user problem the AI feature solves, the data it needs, and how we measure whether it works.
Model Selection
Right model for the job — GPT-4 for language, Vision APIs for images, custom models for domain-specific problems. Cost and latency evaluated.
Integration & Testing
AI integrated into the app and tested against real user data — accuracy, latency, and edge case behaviour reviewed before release.
Monitoring & Optimisation
AI performance monitored post-launch — model drift, cost per call, and accuracy tracked with alerts for when recalibration is needed.
Client Stories
What Clients Say
"The recommendation engine increased average session time by 35% in the first month. Users are discovering products they wouldn't have searched for. That is measurable business value from AI — not just a feature to show investors."
Bilal A.
E-Commerce App, Karachi
"AI triage chatbot handles 60% of initial patient queries before escalating to a nurse. Response time improved, nursing staff freed for complex cases. The AI knows when to hand off — that was the critical requirement."
Yara A.
Healthcare Platform, UAE
"Document classification that used to take a paralegal two hours now takes twelve seconds at 94% accuracy. The AI feature paid for itself in the first week of production use."
Chris B.
Legal Tech App, UK
Pricing
Clear Scope, Clear Price
Single Feature
AI Feature Integration
Timeline: 3–6 weeks
- Single AI feature integration
- Model selection & setup
- API integration & testing
- Fallback behaviour design
- Cost monitoring setup
- Full documentation
- Code ownership
Multiple Features
AI Feature Suite
Timeline: 8–16 weeks
- Multiple AI features
- Custom model fine-tuning (if needed)
- Recommendation engine
- NLP / chatbot integration
- Predictive analytics
- AI monitoring dashboard
- 60-day post-launch support
Need a custom scope? Let's talk.
FAQ
Questions Worth Asking
Yes — AI capabilities can be integrated into apps already in production. We audit the existing codebase and API, identify the cleanest integration points, and add the AI layer without disrupting existing functionality.
It depends entirely on usage volume and the model selected. We estimate API call costs during scoping and design the architecture to minimise unnecessary calls. We also set up cost monitoring so you're never surprised by an infrastructure bill.
Where a general model produces insufficient accuracy for your domain — medical, legal, financial — fine-tuning on your data is available. We scope this separately because it requires a labelled dataset and a longer training process.
AI That Solves Real Problems
Is Worth Building.
Let's Find Yours.
No obligation. No pressure. Just an honest conversation about your project.
We will tell you clearly if we are the right fit.