Answer every question
with #MIND-white on your data.
Incident questions, purchasing advice, or even complex advisory work are ideal for AI, if you feed it with your data, business logic and processes. With you connect sources like SharePoint, email and ERP securely, with roles & permissions, EU data sovereignty and an Audit Trail per answer. Start small and scale once it works.
Why a Chatbot?
Research becomes much faster when #MIND can consult company data and processes in context.
Collect data
Connect the platform to SharePoint, email, your website or ERP. With metadata intelligence, the chatbot understands context (versions, sender, permissions) instead of plain text.
Integrate
Use the chatbot internally or externally without leaking information. Configure roles and permissions so users only see what they are allowed to see, auditable and manageable.
Personalise
Every organisation is unique. Capture tone of voice and writing rules as Skills, so every response sounds like your brand, not generic AI.
Optimise
With feedback sessions and the Audit Trail, we continuously sharpen the chatbot. Source references and substantiation improve, while the tone stays consistent.
Why a Spartner chatbot?
A #MIND chatbot works like a digital colleague who can consult your knowledge, but with control. Available 24/7, in your tone of voice, and with an Audit Trail so you can see what an answer is based on. That improves customer satisfaction and takes pressure off your team by removing routine questions and speeding up complex ones.
Why do we help personally?
A chatbot that only handles standard questions rarely delivers lasting value. The value sits in your business logic, permissions and Skills. That is why we help personally with connecting, digitalising and activating: plugging in sources, setting clear boundaries, and scaling step by step once the output is right.
Benefits of Spartner AI chatbots:
Available 24/7, also outside office hours
Consistent answers that build trust
Faster research with source references and Audit Trail
Less pressure on support and back office
How do you develop a custom AI chatbot?
The real value is in implementation: connecting sources, capturing business logic and activating it safely. Here are the steps we use in practice to make an AI chatbot stick.
Define your needs.
Start with one concrete use case (e.g. service desk, HR, permits). Which questions should the bot handle, which should it not, and which sources are leading? This prevents noise and keeps you in control.
Choose the right technology.
We choose the best-fitting model per task (e.g. GPT, Claude, Llama), while #MIND remains the governance layer: roles, EU data sovereignty, metadata intelligence and an Audit Trail.
Develop the chatbot.
Together with Spartner, you build the chatbot in #MIND as a set of Skills: sources, writing rules, answers and output forms. We align the experience with your brand, but above all with what staff actually need.
Integrate with existing systems.
Connect #MIND to SharePoint, your website, email and ERP/CRM. With roles & permissions, each user only gets access to what is allowed, safe and explainable.
Test and optimise.
Test with real questions from the organisation. Use the Audit Trail to see where context is missing, improve Skills, and set up a feedback loop so quality keeps improving.
Ready to use #MIND for your chatbot?
We do not build a one-off demo, but a chatbot that fits your processes and governance. In an exploratory call we map use cases, data sources and risks. We also show you the Audit Trail, so you immediately feel what “no black box” really means.
The Role of AI in the Future of Chatbots
From loose chat to traceable Skills
The question is not whether AI gets better, but whether you keep it manageable. With #MIND, a chatbot becomes a controlled channel to your own knowledge: connected sources, metadata context, and answers with an Audit Trail. That shifts support from “search and email” to “verify and decide”.
What to expect
We see organisations moving towards more autonomy: bots that propose next steps, prepare documents and signal exceptions. But only when transparency and permissions are standard. That is why the next step is Skills: reusable building blocks that keep improving and lock in your quality standard.
Practical tips for implementing an AI chatbot
How do you make it actually work?
Implementing an AI chatbot is not only technical; it is organisational too. Start with one process, make ownership explicit, and agree what “good” means: source, tone, boundaries and escalation. That prevents disappointment and supports continuous improvement.
Training is essential
Train staff not only in usage, but in judgement: when do you trust an answer, when do you check the source, and when do you escalate? The Audit Trail makes that concrete and repeatable.
Create a feedback loop
Implementation is only the beginning. Track where questions go wrong, adjust Skills, and steer based on feedback. That keeps the chatbot current and quality rising, without losing control.
The benefits of bespoke chatbots
Why choose customisation?
With #MIND, you build bespoke chatbots without starting from scratch each time. You capture business logic, tone of voice and sources as Skills, and you can keep evolving as your organisation grows or processes change.
Customer focus
A bespoke chatbot must understand your questions in context: who is asking, which version is leading, which rule applies. #MIND combines metadata intelligence with source references and an Audit Trail so you can verify and steer.
Boosts efficiency
By automating repetitive searching and standard answers, people can focus on work that requires judgement. Less switching, more progress, and you stay in control.
🤖 How much does a bespoke AI chatbot cost?
The costs of a bespoke chatbot vary depending on the features and technologies selected. It is important to compare quotes from different providers for an accurate estimate.
⏱️ How long does it take to develop a chatbot?
The development time depends on the complexity of the requirements and the integration with existing systems. It usually takes a few weeks to several months.
🔐 Are bespoke chatbots secure?
Yes, provided they are developed properly. Make sure they comply with GDPR rules and that personal data are stored securely.
🌍 Can a chatbot support multiple languages?
Certainly! Bespoke chatbots can be configured to understand and use multiple languages and regional dialects.
🔄 How do I keep the chatbot up to date?
Regular updates and training sessions are necessary to optimise the chatbot based on experience and user feedback.
🚀 What are some examples of use cases?
The applications are numerous: from customer service and order processing to internal communication and HR processes. Every organisation can find its own unique use cases.