We build AI that works in production — automation, agents, and AI-native applications delivered by engineers who have already shipped it.
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Why Mejix
The gap between AI potential and AI in production is where most organisations get stuck. The strategy is clear. The use cases are obvious. But building AI that actually works — that integrates cleanly with existing systems, handles real-world edge cases, performs reliably under load, and delivers measurable business outcomes — requires engineering expertise that most teams don't have in-house yet. Mejix has already built and shipped AI products. We bring that experience directly to your project.
You need this service if:
Your team has identified where AI could save time, improve decisions, or create new product capabilities — but you don't have the machine learning engineers, LLM expertise, or AI product experience to execute. The use case sits on a roadmap, not in production.
Document processing, data extraction, classification, customer query handling, content generation, quality checking — tasks that consume significant engineering or operational time and follow predictable patterns that AI handles well.
Your product needs AI capabilities — recommendations, search, predictions, conversational interfaces, vision — but your current engineering team is focused on the core product and can't take on a parallel AI build without slowing everything down.
You've experimented with ChatGPT wrappers, off-the-shelf AI tools, and prompt engineering. Some of it was interesting. None of it moved the needle. You need AI that is built for your specific use case, integrated into your workflow, and measured against business outcomes — not a demo.
How do we solve
We work across the full AI development stack — from strategic consulting and use case definition through to production-ready AI systems, agents, and applications.
We work with your leadership team to identify the highest-value AI use cases for your business, define what's technically feasible, and build a prioritised AI roadmap — so investment goes where it creates the most impact, not where it's easiest to demo.
We automate complex, high-volume business processes using AI — document understanding, data extraction, classification, approval workflows, and multi-step operational pipelines that currently depend on manual human effort at every stage.
We build autonomous AI agents that can plan, reason, use tools, and complete multi-step tasks without human intervention at every step. Customer service agents, research agents, operations agents, and internal productivity agents — purpose-built for your specific context and workflows.
We integrate large language models — OpenAI, Anthropic, open-source — into your existing products and workflows. Custom AI applications built around your data, your processes, and your users. Not a generic chatbot — a purpose-built AI layer that solves a specific problem.
We build vision-based AI systems for image and video analysis, quality inspection, object detection, and visual search. Yehuda's automated diamond detection system is a live example — computer vision running in production, solving a real business problem at scale.
We build predictive models and AI analytics layers that surface actionable insights from your data — demand forecasting, churn prediction, anomaly detection, personalisation engines. AI that doesn't just describe what happened, but anticipates what happens next.
Obsessed with delivery. Every project, every time.
Key benefits
AI automation eliminates the manual, repetitive work that consumes your team's time. Document processing that took hours takes seconds. Workflows that required human review at every step run end-to-end automatically. The time savings are real and measurable from day one.
AI adds product capabilities that aren't possible without it — visual search, conversational interfaces, real-time recommendations, predictive features. These aren't incremental improvements — they're new dimensions of value your users didn't have access to before.
We don't build AI in isolation. Every system we build is integrated into your existing product, data infrastructure, and workflows — so AI augments what's already working instead of creating a parallel system your team has to manage separately.
We've shipped AI in production — LoveLock, NES, Yehuda's diamond detection. We know where AI systems fail in the real world, how to build for reliability, and how to monitor and improve AI performance after launch. Not just prototypes. Shipped products.
The process
A structured process that moves from use case definition to a production AI system — with evaluation and iteration built in at every stage.
We work with your team to define the specific AI use case — what the system needs to do, what data is available, what success looks like, and what integration points are required. We establish clear acceptance criteria before any model work begins.
We audit your available data — volume, quality, format, and accessibility. For AI systems that require training data or fine-tuning, we define the data requirements and preparation pipeline. We won't start a build on data that can't support it.
We design the AI system architecture — selecting the right models, APIs, and infrastructure for the use case. We evaluate open-source vs. proprietary models, define the inference pipeline, and specify the integration layer before writing production code.
We build the AI system in production-grade code — prompt engineering, RAG pipelines, agent frameworks, API integrations, fine-tuning where required — and integrate it into your product or workflow with proper error handling, fallbacks, and logging throughout.
We evaluate AI performance rigorously — accuracy, latency, edge case handling, and failure modes. AI systems require a different testing approach to traditional software. We build evaluation pipelines that measure what matters and iterate until the system meets the defined acceptance criteria.
We deploy to production with monitoring built in — tracking model performance, input/output quality, latency, and cost over time. AI systems drift. We build the observability infrastructure that lets you see it happening and act before it becomes a problem.
Certifications & Recognitions














Our work
We built a custom computer vision AI system for Yehuda that automates diamond detection and grading — reducing manual assessment time dramatically and enabling the platform to process significantly higher volumes with consistent accuracy.
We built NES from the ground up as an AI-native platform — designed, engineered, and shipped by the Mejix team. An AI application in production, not a prototype.
LoveLock is an AI-powered application built and launched by Mejix — our first fully in-house AI product. Designed, trained, and shipped by the same team that builds AI for clients.
Reviews & Certifications

Mejix has successfully created and launched a functional mobile app, which allows the client to reach and diagnose over 5,000 patients. Despite geographically dispersed clients, the team is accommodating and communicative. They've worked hard to deliver the project on time and within the budget.
Candice Wu
Head of Design, Yehuda
Why Mejix
Everything you need to know about our AI Consulting & Development service.
Whether you're automating a business process, building an AI agent, or embedding AI into your product — we've already built it. Let's talk about what's possible for yours.