1. Executive Summary
As contact centres increasingly adopt generative AI to improve operations, balancing innovation with robust security and compliance has become a critical challenge.
Talkative’s AI-powered platform empowers contact centres to embrace AI confidently, delivering efficiency and exceptional customer experiences while safeguarding sensitive data.
This whitepaper explores Talkative’s approach to data sovereignty and security, showing how organisations can use AI to enhance operations while maintaining the highest standards of compliance and data protection.
Key areas covered include:
- Complete data sovereignty
- Secure AI integration
- Enterprise-grade security
- Real-world success stories
- Talkative’s AI Knowledge Base
By the end of this whitepaper, you will understand how Talkative enables organisations to transform customer engagement securely, giving you the confidence to scale customer contact operations while confidently meeting regulatory requirements.
2. Understanding AI Data Security for Contact Centres
Every customer interaction contains sensitive information, from personal details to transaction records. As such, robust security measures are crucial for protecting sensitive data.
However, when AI processes this data during an automated interaction, the need for added security becomes even more critical.
To ensure utmost security during AI implementations, three key elements must be addressed:
- The first is data protection, which involves safeguarding information from unauthorised access or breaches. This becomes more complex with AI systems that process large datasets.
- The second element is compliance with regulatory bodies / frameworks. For example, the PCI DSS for payment processing and HIPAA compliance for healthcare. Frameworks like these require strict handling of personal data and become even more important when AI systems are involved.
- The third element is data sovereignty, which ensures that customer data is processed and stored according to jurisdictional laws. For example, a European customer’s data must be handled in line with European regulations, even if the organisation itself operates internationally.
Data sovereignty is particularly important because mismanagement can lead to severe legal penalties and reputational damage. Customers must trust that their data is handled securely and in accordance with local regulations.
3. Talkative’s Security Architecture
To meet the three key areas outlined, Talkative provides organisations with full control over their data, ensuring that every interaction is secure, compliant, and reliable.
For AI processing, Talkative offers a choice of models to suit your compliance needs:
- OpenAI’s models process data in US facilities, with all data being encrypted in transit and at rest, and deleted immediately after use.
- Google Gemini provides regional processing instances, ideal for organisations prioritising local compliance.
- For maximum transparency and control, Meta’s LLAMA and Anthropic's models can be deployed on AWS regional instances, allowing organisations to maintain full oversight of their AI workflows and data processing.
This means that organisations can choose where customer information is stored by selecting their preferred AWS regional data centre.
For instance, European businesses can select EU-based data centres to maintain GDPR compliance, while UK businesses have access to dedicated British facilities to meet post-Brexit requirements. Meanwhile, Healthcare providers in the US can utilise storage options that align with HIPAA regulations.
Data Security and Encryption
Regardless of where an organisation chooses to store their data, Talkative’s security measures include end-to-end encryption using trusted Certificate Authorities, ensuring that all data remains protected during transmission for AI processing.
Sensitive data, such as credit card details, are automatically masked prior to processing, preventing agents or systems from viewing private information.
Furthermore, Talkative maintains a strict policy of not using customer data to train any third-party AI models - whether belonging to an AI provider like OpenAI or Talkative’s own software.
This ensures that all customer and company data remains exclusively secure.
Regulatory Compliance
Compliance is built into every feature of Talkative’s platform. For GDPR, this includes data minimisation principles, storage limitations, and comprehensive systems for data access, portability, and erasure.
For PCI DSS, secure workflows and automatic data masking ensure that payment-related interactions meet stringent security standards. Healthcare organisations benefit from proven HIPAA-compliant deployments that protect sensitive patient data throughout AI processing.
Talkative’s disaster recovery framework also ensures business continuity in the event of disruptions. Real-time monitoring tools like CloudWatch and Logz.io provide early warnings, while automated recovery processes restore systems within ten minutes, with a maximum data loss of ten minutes.
Additional safeguards include unique session tokens for all interactions and regular penetration testing to address vulnerabilities proactively.
LLM Guardrails
In the context of using AI for customer service, “hallucinations” refer to instances where an AI model generates incorrect, irrelevant, or fabricated information during a response.
For organisations using AI in their contact centres, this kind of erroneous response can undermine trust, harm customer experiences, and potentially introduce compliance risks.
Talkative mitigates the risk of hallucinations by designing its AI-powered solutions around a secure, private AI Knowledge Base.
This ensures that the AI only draws information from your pre-approved data, such as PDFs, URLs, CSVs, or TXT files.
By operating in a “closed loop,” the system prevents external data from influencing responses, ensuring customer and organisational information remains accurate and protected.
Talkative further enhances accuracy through the use of custom prompts, which serve as essential guardrails for the AI’s behaviour.
These prompts can also help define the chatbot’s tone of voice, character, and response style, ensuring the AI consistently aligns with your brand’s values and communication guidelines.
This feature gives organisations full control over the personality and approach of their AI interactions.
Additional safeguards are also in place to ensure reliability and security, including:
- Seamless handovers to human agents when the AI cannot confidently resolve a query, ensuring continuity in customer support.
- Accuracy reports and customer interaction insights that allow supervisors to monitor performance and identify areas for improvement.
- An AI knowledge testing suite that allows teams to test and improve the accuracy of their AI responses.
With these measures, Talkative provides a robust framework for preventing hallucinations while enabling secure, efficient, and on-brand AI interactions.
By combining custom prompts, a private Knowledge Base, and active oversight tools, Talkative ensures that AI becomes a trustworthy and transformative asset for your contact centre.
4. AI Knowledge Base and Real-World Success
As discussed above, Talkative’s AI Knowledge Base allows organisations to create private datasets for secure AI processing.
By uploading content from URLs or text-based files, organisations can build knowledge bases tailored to their specific needs.
This ensures that AI-generated responses are accurate, on-brand, and based solely on pre-approved data. Human oversight further ensures that updates remain consistent and secure.
For a real-world example of how these systems have successfully supported contact centre teams, Healthspan is a proud advocate of Talkative’s AI capabilities.
Directly integrated into their Mitel MiContact Center Business platform, Healthspan has achieved an impressive 90% AI resolution rate for repetitive customer queries.
At the same time, the team saw improvements in their CSAT scores, as well as a significant increase in response consistency.
Handling over 150,000 interactions every month while maintaining strict adherence to GDPR and PCI DSS regulations, the team were thrilled with their results.
IT Manager Rob King shared:
“Achieving a 90% resolution rate has been massive for Healthspan and our contact centre. Agents now have far more time on their hands to concentrate on other tasks, and with the platform’s live chat and social messaging coming as part of the solution, any AI interaction is always safeguarded with an agent that’s ready to take over…
Overall, getting Talkative’s Generative AI Chatbot is a no-brainer. It’s changed the way we think about AI customer service. It’s mind-blowing to see the responses it gives.”
Building AI Knowledge Bases
Achieving results like Healthspan’s starts with Talkative’s AI Knowledge Base.
In traditional software terms, a knowledge base is a repository of information about an organisation’s products, services, and / or processes.
An AI Knowledge Base is an extension of this concept: a knowledge repository centre that AI can use to automate customer service responses.
Building a robust and secure AI Knowledge Base is a straightforward process with Talkative.
Within the platform, you can build multiple knowledge bases for different interaction queues, teams, and purposes.
This is particularly useful if you serve multiple brands or departments from a single Talkative account.
Uploading Information
Talkative knowledge bases can be created quickly and easily by uploading the following:
- Free text
- Website content (e.g. individual URLs or an entire website scan)
- File-based content (PDF, JSON, TXT, CSV, etc)
- Integration data (CRM, API information, etc)
Knowledge bases that include website content will update automatically at specified intervals to reflect any changes made to the selected URLs.
Your knowledge base input is important because it determines the quality of your AI outputs - from chatbot responses to AI agent suggestions and supervisor insights.
For best results, you should ensure that your knowledge base content is accurate, relevant, comprehensive, and up-to-date.
The following are some examples of essential information/documents to include in your knowledge base...
- Product & Service Descriptions: Detailed information on all your products/services.
- FAQs: A list of frequently asked questions and answers covering common customer inquiries.
- User Guides & Tutorials: Step-by-step instructions or manuals to help users navigate your offerings.
- Company Policies: Documents outlining policies on returns, warranties, and terms of service.
- Pricing Information: Clear pricing structures, fees, or subscription details.
- Privacy & Security Policies: Statements on data protection and user privacy.
- Troubleshooting Guides: Solutions for common technical or service issues.
- Promotional Materials: Current offers, discounts, or special promotions.
- Legal Disclosures: Terms of use, compliance documents, or disclaimers.
Real-time AI processing
Once your AI Knowledge Base is set up, real-time AI processing ensures fast, accurate responses to customer and agent queries.
By leveraging conversational context, relevant knowledge base data, your custom prompts, and large language model (LLM) technology, the system processes queries and delivers tailored responses in seconds.
Below is a step-by-step breakdown of how this works:
- Query Initiation: A query (customer or agent-driven) is input into the system. This query includes metadata like the question, transcript details, timestamp, or URL to provide contextual relevance.
- Query Input Processed: The system sends the query along with retrieved augmented generation (RAG) chunks (i.e. relevant parts of the knowledge base) to the Large Language Model (LLM). A specific instruction is included, such as: “Does the answer exist in the knowledge base? If not, respond with $unsure.”
- LLM Inference: The LLM processes the input using the conversation context, uploaded knowledge, and relevant custom prompts to determine whether it can retrieve a response from the knowledge base.
- Response Generation: The LLM generates an output that either provides a relevant response based on the knowledge base and context or returns $unsure if it cannot confidently determine an answer from the available data.
- Optional Rephrase: If the chatbot rephrase feature is enabled, the AI-generated response is further refined for clarity, tone, or style.
- Response Delivery: The final response (rephrased or original) is presented to the customer or agent in real time.
- AI Data Deletion: While the customer receives their answer, the data used to achieve the LLM’s answer is deleted. No third-party tools or AI models are trained on the data.
- Interaction Continues: The above process repeats until the interaction reaches a satisfactory end for the customer.
This streamlined workflow ensures that every query is handled efficiently and accurately, empowering your team to deliver faster resolutions and better customer experiences.
5. Conclusion
As we have seen, implementing AI in contact centres comes with unique challenges, including:
- The need for robust data security
- The ability to meet regulatory compliance
- The capability to safeguard against AI inaccuracies like hallucinations
For organisations looking to solve these challenges, Talkative offers a comprehensive solution that meets these needs.
By providing customisable data sovereignty options and secure integrations with leading AI models, Talkative ensures that your customer data remains protected at every step.
Features such as end-to-end encryption, private AI Knowledge Bases, and custom prompts empower organisations like yours to embrace AI while maintaining full control over their data.
In turn, your organisation can deliver secure and satisfying AI-powered interactions that streamline operations and improve the customer experience - empowering your team to leverage AI with confidence.
To learn more about how Talkative can support your organisation, contact us today to schedule a step-by-step demo, or begin your proof of concept trial.
