Introduction
In modern e-commerce, the ability to offer personalized customer service 24/7 is now a basic requirement. private AI Talos, Fixit EE’s solution, combines the power of artificial intelligence with complete control over data, offering advantages that typical cloud chatbots cannot provide. In addition, the Talos integration allows for automatic optimization of sales processes, reducing response time and enhancing customer satisfaction.
What is private AI and how does Talos work?
Definition of private AI
Private AI refers to artificial intelligence that runs in a customer-exclusive environment — either on-premise or in a private cloud. Unlike public services, data is processed without being leaked to third parties, ensuring compliance with GDPR and other regulatory requirements. This architecture also allows for the implementation of internal security policies, such as domain-level encryption, role-based access controls (RBAC), and regular vulnerability assessments.
Additionally, private AI enables the enterprise to maintain a fully auditable historical database, which facilitates internal analysis and record-keeping for accounting or legal purposes. Independence from external providers also reduces the risk of «vendor lock-in,» allowing the infrastructure to be adapted to future needs.
The architecture of Talos
Talos integrates with Magento and WooCommerce through special plugins that communicate with a dedicated AI server. The solution includes:
- Language model adapted to Greek language and local vocabulary, which has been trained on e-commerce data, such as product descriptions, reviews and FAQs.
- Interfacing with the product, inventory and order system, ensuring that AI responses are always in sync with the current inventory status.
- Ability to train with historical e-shop data for more accurate answers, including purchasing patterns, frequent shipping issues, and customer preferences.
- Compatibility with third-party APIs, such as ERP, CRM and inventory management systems, so that AI can provide comprehensive information (e.g. shipping status, availability in specific stores).
Talos infrastructure runs in Docker containers or VMs, offering flexibility in choosing the execution environment. Auto-scaling allows CPU/Memory resources to be adjusted based on traffic without impacting performance or security.
Advantages of private AI vs. public cloud chatbot
Data security and privacy
With private AI, all personal customer information, including order details, remains within the company’s network. The solution is fully compliant with data protection regulations, reducing the risk of a breach. In addition, the platform supports end-to-end encryption (TLS 1.3) for all communications and offers data-at-rest encryption with AES-256.
The ability to manage logs internally allows for the immediate detection of suspicious activity through SIEM (Security Information and Event Management) tools, while the data purge capability ensures that data is deleted in accordance with GDPR retention policies.
Personalization and performance
Talos can be trained on your own product, price, and return policy data, delivering answers that accurately reflect your store’s actual offerings. Performance improves as the model learns from your customers’ interactions. Each time a customer asks a question, the system stores the query and the corresponding answer, allowing for iterative optimization through reinforcement learning techniques.
Another advantage is the ability to create custom conversation flows by product category or customer type (e.g. B2B vs. B2C). This way, Talos can tailor the tone, complexity, and level of detail of the response based on the user’s profile.
Cost control and scalability
Unlike pay-per-use cloud service models, Talos' private AI operates with a fixed maintenance cost, while scaling is done internally, adapting resources to the needs of the e-shop. The initial investment covers installation, model training and licensing, while monthly expenses are limited to infrastructure costs (server, storage, backup).
The cost forecasting feature through the dashboard allows the administrator to plan expenses accurately, avoiding unexpected increases that often occur in cloud solutions based on the number of requests or traffic spikes.
| Parameter | Private AI (Talos) | Public Cloud Chatbot |
|---|---|---|
| Data privacy | Full control within the business | Data stored with third parties |
| Personalization | Training with your own data | Limited customization |
| Operating costs | Fixed, no variable charges | Variable, per use or per month |
| GDPR compliance | 100 % within your network | Depends on the provider |
Talos Integration with Magento & WooCommerce
Connecting to WooCommerce via Talos Theme
Η Talos WooCommerce Theme (€60.76) includes the AI assistant built in. Installation is done in three steps:
- Install the theme and activate the "Talos AI" plugin.
- Connecting the AI server to the WooCommerce APIs (products, inventory, orders).
- Configure custom dialog flows via the admin panel.
During configuration, you can define triggers (e.g. «low stock», «promotion», «FAQ») so that the AI automatically suggests relevant actions or offers. Additionally, the integration supports multiple languages, allowing for customer service in Greek, English and other languages with a single system.
Magento implementation
For Magento, Fixit provides an integration package that connects private AI to product, category, and customer modules. The solution supports both Magento 2.4+ and PWA storefronts, enabling a similar AI experience across all channels. The installation includes a Composer package, a CLI script to initialize API connections, and a UI component to manage dialog scripts.
Developers can extend functionality through custom extensions so that AI can provide information such as real-time shipping status, availability in physical stores, or even cross-selling suggestions based on purchase history.
Performance and monitoring
With Talos, you can monitor interactions in real time through a dedicated dashboard. Usage data helps to further optimize dialogue scenarios and detect potential service issues. The dashboard displays KPIs such as average response time, resolution rate, and customer satisfaction (CSAT) collected after each conversation.
- Real-time notifications for API failures or excessive latency.
- Ability to export reports to CSV/Excel for analysis by the marketing department.
- Integration with observability tools like Grafana or Prometheus for advanced resource monitoring.
Implementation stages and best practices
Needs analysis and planning
The process begins with an assessment of business requirements: types of customer questions, critical data that needs to be secured, and desired level of automation. The result is a dialogue flow map tailored to your business. At this stage, it is recommended to involve customer service, IT, and compliance departments to identify critical touchpoints.
Additionally, the analysis includes competitor research to identify gaps in current service and design unique features (e.g., customized offers based on purchase history).
Model development, testing and training
In this phase, the AI model is trained with samples from the history of questions and orders of the e-shop. At the same time, tests are carried out in a controlled environment (staging) to ensure the accuracy of the answers and the stability of the system. The tests include:
- Unit tests for each API integration.
- Load testing with peak traffic scenarios to verify scaling.
- User Acceptance Testing (UAT) with real service representatives to assess the naturalness of the dialogues.