AI-Powered Applications

AI-Powered Application Development

Build next-generation applications with integrated AI — from real-time language processing and voice interfaces to computer vision and predictive analytics for web and mobile.

AI Application Capabilities

Integrate cutting-edge AI into every layer of your product

Real-time AI Processing

Stream AI-generated responses, classifications, and decisions directly into your application with low-latency APIs and WebSocket integrations.

Voice Interfaces

Speech-to-text and text-to-speech capabilities for hands-free applications, call centre bots, voice assistants, and accessibility-first products.

Computer Vision

Image recognition, object detection, OCR, and video analysis integrated into web and mobile apps using state-of-the-art vision models.

Predictive Analytics

ML-powered forecasting and anomaly detection embedded in your dashboards to surface actionable insights from your business data.

Mobile Optimization

On-device AI inference for privacy-sensitive use cases and offline functionality — optimized for iOS and Android performance budgets.

Cloud Deployment

Scalable AI application infrastructure on AWS, GCP, and Azure — auto-scaling, load balancing, and cost-optimized model serving.

Why Choose BitPixel for AI Applications?

We bridge the gap between AI research and production products — turning model capabilities into features users actually love, at the speed your business demands.

Full-stack AI application development
LLM, vision & speech model integration
Streaming & real-time UI patterns
Model hosting & cost optimization
Mobile-first AI experiences
Privacy-compliant data handling
A/B testing for AI features
Observability & error tracking
Iterative improvement cycles
Free AI feasibility assessment

Our Tech Stack

OpenAI / Anthropic APIsWhisper / ElevenLabsVision TransformersReact / Next.jsReact Native / FlutterFastAPI / Node.jsAWS SageMakerVercel AI SDKWebSocketsPostgreSQL / Vector DB

Our Development Process

1

Discovery

Identify AI use cases, data availability, and success metrics

2

Prototyping

Rapid proof-of-concept to validate AI capabilities

3

Evaluation

Accuracy, latency, cost, and safety testing

4

Launch

Production deployment with monitoring and iteration

Frequently Asked Questions

Answers to the most common questions about this service.

AI application costs depend heavily on the type of AI feature, the underlying model, and the complexity of the surrounding application. An AI-powered feature added to an existing app starts around $10,000. A full AI-native application with voice, vision, or predictive capabilities typically ranges from $30,000–$120,000+.

Adding a single AI capability (e.g. a recommendation engine or document summariser) to an existing app takes 4–8 weeks. Building a full AI-native application from scratch — with data pipelines, model integration, UI, and deployment — typically takes 12–24 weeks.

We integrate a broad range of AI capabilities: natural language processing and summarisation, voice interfaces (speech-to-text and text-to-speech), computer vision (object detection, OCR, image classification), recommendation engines, predictive analytics, and generative AI for content or image creation.

Yes, this is one of our most common engagements. We audit your existing codebase, identify the best integration points, and add AI capabilities as modular services via API — minimising disruption to your current architecture and allowing incremental rollout.

We design with privacy by default: on-premise or private-cloud model deployment where sensitive data must not leave your infrastructure, data minimisation, encryption at rest and in transit, and role-based access controls. We can work within GDPR, HIPAA, and SOC 2 requirements.

We use Python (FastAPI, Flask) for AI backends, React/Next.js for frontends, and deploy on AWS, GCP, or Azure. For AI, we use OpenAI, Anthropic, and Hugging Face APIs alongside frameworks like LangChain, LlamaIndex, and PyTorch for custom model work.

What Clients Say About This Service

Real feedback from businesses that have used this service.

BitPixel built a multi-agent AI system that handles 80% of our customer queries automatically. Response time dropped from 4 hours to under 2 minutes. The ROI was visible within the first month.

SC

Sarah Chen

CTO, TechFlow Solutions

BitPixel delivered an AI-powered product recommendation engine that increased our average order value by 34%. The 3D product configurator they built alongside it is genuinely breathtaking. Users spend twice as long on product pages now.

AD

Amara Diallo

Product Manager, Visionary Apps

Ready to Build Your AI Application?

Get a free AI feasibility assessment and discover what's possible for your product.