Beyond the Hype: Practical AI Engineering
Artificial Intelligence is no longer sci-fi; it is the new electricity. However, the path from a "cool demo" to a production-grade system is fraught with challenges: data privacy, hallucination, latency, and cost. At Codexal, we bridge this gap.
We don't just "wrap" APIs. We build robust AI Pipelines that clean data, engineer prompts, fine-tune models, and monitor performance in the real world. Our solutions are designed to be explainable, ethical, and aligned with your business KPIs.
1. Generative AI & Large Language Models (LLMs)
Unlock the potential of generative text with custom solutions built on top of GPT-4, Claude, or open-source models like Llama. We specialize in RAG (Retrieval-Augmented Generation), which allows AI to answer questions based on your data, not just general internet knowledge.
- Internal Knowledge Bases: Turn your PDFs, Slack logs, and Notion pages into a searchable, chat-able brain for your company.
- Customer Support Automation: Build agents that can triage tickets, draft responses, and even take actions like refunding orders autonomously.
- Content Generation: Automate the creation of SEO articles, product descriptions, and personalized marketing emails at scale.
2. Optical Character Recognition (OCR)
Data entry is the bottleneck of modern business. Our **Intelligent Document Processing (IDP)** solutions use state-of-the-art computer vision to extract structured data from unstructured documents with over 99% accuracy.
- Finance Automation: Automatically process invoices, receipts, and purchase orders, syncing them directly to your ERP or accounting software (Xero, QuickBooks, SAP).
- KYC & Identity: Instantly verify user identities by extracting data from Passports, ID cards, and Driver's Licenses, including Arabic text support.
- Handwriting Recognition: digitize legacy forms and handwritten notes, unlocking decades of archived data.
3. Computer Vision & Predictive Analytics
Give your systems the ability to "see" and "foresee". We build models that analyze images, video feeds, and historical data patterns.
- Quality Control: Use cameras to detect defects in manufacturing lines in real-time.
- Safety Monitoring: Detect PPE usage or unauthorized access in construction sites and secure facilities.
- Demand Forecasting: Analyze sales history to predict future inventory needs, reducing stockouts and overstock.
Our AI Implementation Process
- Data Audit: We assess your data quality and availability. AI is only as good as the data it learns from.
- feasibility Study: We prove the concept with a rapid prototype to ensure the problem is solvable within budget.
- Model Development: We select the right architecture (Transformer, CNN, RNN) and train/fine-tune it on your dataset.
- Integration: We wrap the model in a scalable API and build the frontend interface for your users.
- MLOps & Monitoring: We deploy monitoring tools to detect "drift" (when model performance degrades over time) and retrain automatically.