Agentic AI refers to autonomous systems that don't just answer questions but take action. Unlike traditional chatbots, AI Agents can interact with your software, manage workflows, and execute multi-step tasks (like processing invoices or scheduling fleets) without human intervention, significantly reducing operational costs.

Security is our priority. We implement Private LLM instances and RAG (Retrieval-Augmented Generation) architectures. This ensures your proprietary data stays within your secure cloud environment and is never used to train public models, maintaining 100% data sovereignty.

Yes. We specialize in bespoke machine learning models tailored for logistics, e-commerce, and healthcare. We use frameworks like TensorFlow and PyTorch to build models that solve domain-specific problems, such as route optimization or predictive demand forecasting.

Generative AI (like ChatGPT) creates new content—text, images, or code. Predictive AI analyzes historical data to forecast future outcomes, such as predicting when a machine might fail or identifying which customers are likely to churn. Layercodes integrates both to create a holistic intelligent ecosystem.

A standard AI integration (like an intelligent chatbot or automated workflow) takes 4 to 8 weeks. Developing a custom-trained neural network or a complex Agentic system usually ranges from 3 to 6 months depending on the data complexity.

Absolutely. Our AI solutions are designed to be "layer-compatible." We use robust API architectures to connect AI intelligence directly into your existing tools like SAP, Salesforce, or custom-built legacy systems, ensuring a seamless data flow.

We use Fact-Grounding and Verification Loops. By implementing RAG architectures, we force the AI to only provide answers based on your verified documents. We also add "Human-in-the-loop" checkpoints for high-stakes decision-making.

Not necessarily. Using Transfer Learning, we can take powerful pre-trained models (like Llama 3 or Claude) and "fine-tune" them with a relatively small amount of your specific data to achieve highly accurate, custom results.

Ongoing costs usually involve API tokens (if using providers like OpenAI/Anthropic) or GPU cloud hosting (if running custom models on AWS/Azure). We optimize our code to minimize token usage and maximize computational efficiency to keep your OPEX low.

We are an Engineering-First firm. While many agencies just "resell" API access, we build the underlying architecture. Our deep background in logistics and product development means we understand how to apply AI to solve real-world revenue problems, not just provide "cool" features.