AI-Powered Application Development

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 $2,000. 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.

Yes. We build full AI SaaS platforms end-to-end — from architecture design and AI model integration to multi-tenant user management, billing (Stripe), admin dashboards, and cloud deployment. Our AI SaaS builds include usage metering, API rate limiting, and scalable infrastructure from day one.

Yes. We build recommendation engines using collaborative filtering, content-based filtering, and hybrid approaches powered by machine learning. These engines personalise product suggestions, content feeds, search results, and user experiences — driving higher engagement and conversion rates.

Absolutely. For organisations with strict data sovereignty requirements, we deploy open-source AI models (Llama, Mistral, Whisper) on your own infrastructure — on-premise servers, private cloud, or air-gapped environments. Your data never leaves your network while still benefiting from AI capabilities.

We add AI as a modular microservice connected via API, so your existing application architecture stays intact. Common integrations include AI-powered search, auto-categorisation, content generation, document summarisation, and intelligent routing. We handle the AI backend; your frontend calls our API endpoints.

Yes. We build AI lead generation automation systems that qualify leads using AI scoring, enrich contact data, automate outreach sequences, and route high-intent prospects to your sales team. Our lead gen automations integrate with your CRM, email, and LinkedIn to create a fully automated sales pipeline.

Yes. We build automated reporting dashboards that use AI to surface insights, detect anomalies, and generate narrative summaries. These AI-powered dashboards pull data from multiple sources (CRM, analytics, finance tools), update in real time, and deliver actionable insights — not just charts.

Yes. We build React Native AI-powered app development projects that combine cross-platform mobile development with AI capabilities like image recognition, voice assistants, natural language processing, and personalised recommendations. React Native lets us deliver AI-enhanced apps for both iOS and Android from a single codebase.

Yes. We build custom AI solutions for the healthcare industry including patient triage chatbots, medical document processing, appointment scheduling automation, HIPAA-compliant data handling, and predictive analytics for patient outcomes. All healthcare AI solutions are built with strict data privacy and compliance requirements.