WORKFLOX Services
Build AI Apps That Work
In Production, Not Just In Demos
Most AI projects fail before launch. We build AI-powered applications that are production-ready, secure, and scalable — integrated into your real business workflows from day one.
The Challenge
Why Most AI Projects Fail
- ✗Prototype-quality output shipped as 'production' systems
- ✗AI features with no connection to real business logic
- ✗LLM hallucinations not caught before they reach customers
- ✗No fallback when the AI model is unavailable or wrong
- ✗Vendor lock-in with no control over your own data
Our Approach
The WORKFLOX Difference
- ✓Production-hardened AI architecture with fallback logic
- ✓Model-agnostic builds — switch GPT-4o to Claude without rewriting
- ✓Prompt engineering and output validation built in
- ✓Your data stays on your infrastructure (self-hosted option)
- ✓60-day post-launch support included
Use Cases
What We Build For You
AI Document Processing
Automatically extract, classify, and route data from invoices, contracts, and forms using GPT-4o or Claude.
AI-Powered Dashboards
Give your team natural language access to their data. Ask questions, get insights — no SQL required.
Intelligent Customer Support
Deploy AI agents that resolve Tier-1 tickets, escalate to humans, and learn from your knowledge base.
AI Content Pipelines
Automate content creation, localisation, and personalisation at scale with LLM-powered workflows.
Recommendation Engines
Build product recommendation, content matching, and user personalisation systems using embeddings and vector search.
AI Voice Assistants
Build voice interfaces that understand natural language and integrate with your existing backend systems.
Technology
Our Stack
We select the best tool for each job — not the most fashionable one. Every technology choice is justified by your performance, security, and maintainability requirements.
FAQ
Frequently Asked Questions
What AI models do you use for app development?
We are model-agnostic. We primarily work with OpenAI GPT-4o, Anthropic Claude 3.5, and Google Gemini depending on the use case, latency requirements, and data privacy constraints. We can also deploy open-source models like Llama 3 on your own infrastructure.
How long does it take to build an AI app?
A focused MVP with one AI feature typically takes 6–10 weeks. Enterprise-grade AI applications with RAG, custom training, and integrations typically require 12–20 weeks. We provide fixed-milestone timelines in every proposal.
Can you integrate AI into our existing application?
Yes. Most of our engagements involve integrating AI into existing products rather than building from scratch. We audit your current stack, identify the highest-impact AI touchpoints, and integrate without breaking existing functionality.
Is our data safe when using AI APIs?
We implement enterprise data handling by default: no training opt-in on OpenAI's business API, encrypted transit and storage, and self-hosted LLM options for sensitive workloads. We can deploy on your own AWS or Azure environment.
Do you build AI apps for both web and mobile?
Yes. We build AI-powered web apps (React, Next.js), mobile apps (React Native, Flutter), and backend services (Node.js, Python). The AI layer integrates across all platforms.
Ready to Build?
Let's Start With a Free Scoping Call
Tell us what you're building. We'll scope it, advise on the right approach, and give you a fixed-price proposal — no commitment required.
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Have A Project?
Let’s Build ItHave a project in mind? Tell us what you're building and we'll get back to you within 12–24 hours with a clear plan.
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12–24 Hr Response
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60-Day Bug Fix
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