Lower operating costs
The bot handles enquiries at any hour, automates routine tasks and takes on summarisation and text generation, so your staff can focus on work that needs them.
AI chatbots · Customer engagement
AI Chatbot Development Services for customer service and sales
We build custom AI chatbots that answer your customers around the clock, guide them through the sales process and recommend the right products. Each bot is trained on your own product data and customer interactions and runs on the channels your customers already use.
- Answers to customer queries 24/7, in several languages
- Recommendations based on past interactions
- One bot across web, app, social media and CRM
- 57% of our team hold a PhD
- German company, working under the GDPR
Discuss your project
5.0 18 reviews on Clutch Go Global Awards winner
Trusted by enterprises, scale-ups and non-profits
What you gain
What a customer-facing chatbot changes
Chatbots pay off where conversations are frequent, repetitive and close to revenue.
Faster, personal answers
Customers get an immediate answer and recommendations based on their history and preferences, which builds loyalty and improves retention.
More conversions
From form submission to checkout, the chatbot keeps hesitant buyers engaged with real-time information and personalised suggestions instead of leaving them unattended.
What we deliver
Chatbots we build
From GPT-based assistants to bots for social channels, each one is designed around the conversations your customers actually have.
- 01
GPT-based chatbots
Conversational agents on GPT models, including ChatGPT, for customer support, personalised recommendations and content generation.
- 02
Customer service and CRM chatbots
Bots trained on your product data and customer interactions, drawing on your CRM so answers are accurate and specific to each customer.
- 03
Social media bots
Chatbots for Facebook, Instagram and LinkedIn that start and carry conversations with your target audience.
- 04
AI virtual assistants
Assistants inside your workflow that provide information, manage schedules and handle tasks, and learn from user interactions.
- 05
Multi-language support and NLP
Natural language processing that understands intent and context in different languages, so you can serve customers in new markets.
- 06
Sentiment analysis
The bot reads emotions, opinions and attitudes in user messages and adapts the conversation accordingly.
- 07
Omnichannel integration
One consistent brand experience across your website, mobile app, social media and CRM, with smooth hand-over between channels.
- 08
Secure customer interactions
Controlled access and secure storage protect sensitive customer information, so the bot can also support e-commerce and financial interactions.
- 09
Chatbot strategy consultation
We analyse your requirements and objectives and advise on chatbot strategy, development and implementation before anything is built.
Technologies we work with
- Python
- GPT-3
- ChatGPT
Not sure which of these you need? Describe the problem and we will recommend the approach.
Discuss your projectCase studies
All case studiesResults we delivered for our clients
Internet and Tech · NLP
NLP chatbot for centralised meeting scheduling
3,000man-hours saved per month
A natural language processing chatbot for a centralised meeting scheduling system that automated the process and reduced the number of human operators needed.
Read the case study
Custom LLM chatbot with document references for a consulting firm
In-house LLM no reliance on third-party LLM services
A private, hosted chatbot built on a custom large language model, giving a consulting firm answers with source references while keeping full control over its data.
NLP skill gap analytics for a science and technology company
~10,000 man-hours saved
An interactive NLP tool that assesses employees' skills, compares skill profiles and identifies skill gaps between business-critical staff and their potential successors.
Semantic company search for private equity deal sourcing
1 week of analyst work saved per new niche market
An end-to-end NLP solution that lets private equity funds and venture capital firms find and cluster relevant companies by meaning rather than by industry code or keyword.
Why AI Superior
Research-grade AI, delivered like a product company
Many vendors can build a demo. Making AI work reliably on real data, inside real business processes, is the hard part, and it needs a different kind of team.
01
A research-led team
AI Superior was founded in 2019 by AI researchers with published papers and patents, and the whole team works to that research standard.
- PhD57%
- MSc28%
- BSc15%
02
Built to reach production
Every project is de-risked in stages, with a go/no-go decision at each milestone, so budget only goes into approaches that have worked on your data.
4× our proof-of-concept success rate compared with the market average
03
A complete team from day one
Strategy, models and software are designed by one team, so nothing gets lost in hand-overs between vendors.
- Product AI product owner, business analyst, project manager
- Data Data scientists, ML engineers, BI analyst
- Development Software engineers, QA, DevOps
04
Your data stays under control
When data must not leave your organisation, we build on private, self-hosted models instead of third-party AI services.
- GDPR, German company
- Self-hosted LLMs
- Transparent methods
Our team
The experts behind your project
Your project is led by senior data scientists and engineers with research backgrounds, supported by our product and development teams.
-
Dr. Sergey Sukhanov Chief Data Scientist PhD in Machine Learning, data scientist since 2013. Publications, patents and 30+ implemented AI use cases; several IEEE awards.
-
Dr. Ivan Tankoyeu Chief Data Officer PhD in Computer Science. Recognised by the IEEE GRSS Society, winner of the Global AI Hackathon 2017, Kaggle TOP500 data scientist (2014).
-
Sergio Frayle, M.Sc. Lead Data Scientist Master’s in AI, Pattern Recognition and Digital Imaging; 7+ years in image processing and computer vision, with publications.
-
Enrique Fernández, M.Sc. Senior ML Expert Master’s in Robotics and Mechatronics; builds and deploys complex AI solutions, particularly in computer vision and NLP.
-
Peter Luck, M.Sc. AI Consultant Master’s in Business Engineering and Computer Science; product and project manager for machine-learning products.
Client reviews
5.0 Rated 5.0 by the people we build for
18 verified reviews on Clutch
“Overall, our experience with AI Superior has been extremely positive, and we have been highly satisfied.”
Delivered a highly specialized AI chatbot with custom AI logic for a foundation supporting children and young adults.
“They are not only great theoretical experts, but also deliver with their awesome hands-on skills.”
“AI Superior showed a strong commitment to delivering high-quality solutions to us.”
Improves and maintains the data infrastructure of a credit solutions company: data pipelines, ML models and custom reports.
How we work
A staged AI project life cycle
Every stage ends with a result you can check, and you decide on the next one only after seeing the previous one work. You keep control of scope and budget.
- Estimate before you commitYou see scope and expected results before the build begins.
- Go/no-go after every stageEach stage ends with a result you can check and a decision on the next step.
- Risks reported openlyWe share risks and opportunities as soon as the analysis shows them.
- Go / no-go decision
Discovery
We work through the business problem with your team and define the direction of the solution.
You get: Scope, approach and a high-level estimate of effort and expected results
- Go / no-go decision
Data and feasibility
We get to know your team and data and check whether AI is the right tool for this problem.
You get: A data assessment and a clear feasibility verdict before any build starts
- Go / no-go decision
Proof of concept / MVP
We start small, using the data already available, to test the solution in practice.
You get: Measured results on your own data and a basis for the investment decision
- Go / no-go decision
Integration and scaling
We integrate the solution into your existing systems, fine-tune the models and adjust them where needed.
You get: A solution running inside your processes, compatible with your data and systems
-
Evaluation
We review the results with you and make sure they are read correctly.
You get: What the solution delivered and where to improve next
Use cases by industry
Chatbots for customer-facing industries
Where chatbots take load off service teams and move customers towards a purchase.
E-commerce
Personalised product recommendations and real-time suggestions that improve satisfaction and drive conversions.
- Product recommendations
- Real-time suggestions
- Order tracking
Marketing and Sales
Real-time assistance on your chosen platform to generate leads and keep prospects engaged.
- Lead generation
- Automated follow-ups
- Targeted promotions
Banking
Round-the-clock customer support while maintaining regulatory compliance and data security.
- Complaint handling
- Fund transfers
- Balance enquiries
- 24/7 customer support
Healthcare
Smoother interaction between patients and providers, improving access to care.
- Appointment scheduling
- Medication reminders
- Symptom analysis
Insurance
Immediate assistance for clients on the processes they contact you about most.
- Policy renewals
- Policy enquiries
- Claims processing
Travel
Bookings, recommendations and live updates in one conversation.
- Customer bookings
- Travel recommendations
- Real-time travel updates
- Payment handling
Supply Chain
Instant access to real-time information for customers and dealers alike.
- Delivery status updates
- Order tracking
- Inventory management
Awards and recognition
Ranked among the top AI companies
Recognised by international business awards and by independent B2B platforms that rank companies on verified client reviews.
-
Go Global Awards Winner 2021 · International Trade Council -
Best Data Science & AI Service Provider, Europe 2021 · German Business Awards -
Top Artificial Intelligence Company 2023 · Clutch -
Top Machine Learning Company 2023 · Clutch -
Clutch Champion Fall 2023 · Clutch -
Clutch Global Fall 2023 · Clutch -
Top BI & Big Data Company Germany 2023 · Clutch -
Top IT Services Company Germany 2023 · Clutch -
Top Artificial Intelligence Companies 2023 · TrueFirms -
Top Machine Learning Companies 2021 · Techreviewer -
Most Reviewed IT Services Companies Germany · The Manifest
What is the difference between an AI chatbot and a rule-based chatbot?
A rule-based chatbot reacts to keywords with predefined responses. An AI chatbot uses natural language processing to interpret meaning and context, and learns from previous interactions. Choosing between the two is an explicit step in our process, based on your use case.
How is an AI chatbot different from conversational AI?
Conversational AI is the broader technology that recognises and responds to human text and speech, for example in voice assistants or messaging bots. AI chatbots are one form of it. Not every chatbot is conversational AI: rule-based bots only follow keyword triggers.
How do you build a customer-facing chatbot?
We start with your business goals, the bot's purpose and the key user interactions. We then choose the technology, design conversation flows in your brand voice, train the model on relevant data including your industry terminology, and test it across scenarios. Finally we deploy it on your channels and keep improving it based on user feedback.
Which channels can the chatbot run on?
Your website, mobile or web app, social media channels such as Facebook, Instagram and LinkedIn, and your CRM. We design the bot so customers get a consistent experience whichever platform they choose.
Can the chatbot handle sensitive customer data?
Yes. Our chatbots use controlled access and secure storage to protect customer information, which makes them suitable for e-commerce and financial interactions.
How long does it take to build an AI chatbot?
It depends on the level of customisation, the complexity and the features you need. A basic chatbot can take a few weeks; a more advanced one a couple of months. We set the timeline once we understand your requirements.
What happens after launch?
We monitor performance and user engagement in real time, handle issues, implement updates and refine the bot's responses based on how customers actually use it.
Start your project
Tell us what you want AI to do for your business
Share a few details and our AI team will take it from there. Here is what happens next:
- We review your request and reply by email.
- A call with an AI expert to understand your problem, data and goals.
- A clear recommendation: the approach we suggest and a high-level estimate.
Prefer to pick a time yourself?
Schedule a call