Automated customer support
Enquiries are handled and issues resolved in real time, around the clock. Response times fall and human agents are left with the complex cases.
AI chatbots · Architecture and integration
AI Chatbot Development Services built into your business systems
We design, train and deploy AI chatbots that work inside your operations: connected to your CRM, ERP and workflows, governed and secured, and tested as an MVP before they scale. Our team of AI engineers, data scientists and chatbot developers builds the models behind the conversation, not just the interface.
- Chatbots connected to your CRM, ERP and workflows
- MVP first, scaled only once it is validated
- Continuous monitoring and model refinement
- 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 an integrated chatbot delivers
Personalised engagement
The chatbot analyses user preferences and adapts its answers, supporting conversion and long-term customer relationships.
Streamlined processes
Repetitive tasks, appointments and transactions run through the chatbot across websites, mobile apps and messaging channels, reducing operational costs.
What we deliver
Our chatbot engineering competences
Everything needed to take a chatbot from architecture to a governed system in production.
- 01
Chatbot architecture design
Chatbot architectures designed around your business needs, so the bot fits into your existing systems and user journeys.
- 02
Natural language understanding
NLU that interprets human language reliably, for natural conversations and accurate handling of user requests.
- 03
Machine learning model development
We build and train the models that power automated responses, contextual understanding and accuracy.
- 04
Data engineering and model training
We collect and clean your data and use it to train the chatbot, so its answers are accurate and efficient.
- 05
Integration with CRM, ERP and business systems
The chatbot connects to your CRM, ERP and other systems, so conversations trigger real actions in your workflows.
- 06
Lead generation and sales support
Conversational flows that capture and qualify leads, recommend products, assist with transactions and support checkout.
- 07
Intelligent virtual assistants
Assistants that handle scheduling, reminders and personalised recommendations for customers or employees.
- 08
Edge AI for real-time interactions
Chatbots optimised for edge computing, responding on-device with minimal latency and resource use.
- 09
AI security, ethics and governance
Security measures that protect the chatbot from vulnerabilities and support data protection compliance, plus ethical AI frameworks for responsible and fair interactions.
- 10
Optimisation and performance tuning
We monitor live interactions and refine responses and models to improve accuracy and user satisfaction over time.
Technologies we work with
- GPT
- BERT
- Dialogflow
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
Professional Services · Generative AI, NLP
Custom LLM chatbot with document references for a consulting firm
In-house LLMno 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.
Read the case study
NLP chatbot for centralised meeting scheduling
3,000 man-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.
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.
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, takes a different kind of team. This is what you get with us.
01
Scientists, not generalists
AI Superior was founded in 2019 by AI researchers with published papers and patents. That depth runs through the whole team.
- 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 goes only into solutions proven 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 together, not handed over between separate 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.
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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.
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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).
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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.
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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.
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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.
“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.
“They are not only great theoretical experts, but also deliver with their awesome hands-on skills.”
How we work
A proven AI project life cycle
Every stage ends with a result you can check. You never commit to the next stage before seeing the previous one work, so scope, budget and risk stay under your control.
- 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
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Evaluation
Together we evaluate the results of the implementation and make sure they are interpreted correctly.
You get: A clear picture of the value delivered and where to improve next
Use cases by industry
How we implement chatbots across industries
Examples of chatbot use cases in each sector, from customer service to internal operations.
Insurance
Better customer interactions, automated claims and support for risk assessment.
- Policy support chatbots
- Claims processing with AI-generated reports
- Fraud detection support
- Personalised policy recommendations
Finance
Automated customer service, insights and compliance support for financial institutions.
- Financial advisory chatbots
- Transaction support
- Fraud detection support
- Personalised investment recommendations
Pharmaceuticals
Chatbots and data insights for research and patient care.
- Patient engagement
- Clinical trial assistance
- Medical documentation automation
Government
Efficiency, transparency and public engagement for government agencies.
- Policy and citizen support chatbots
- Document processing automation
- Public service chatbots
Construction
Assistants for planning, safety and project management.
- Virtual assistants for site monitoring
- Safety alerts and compliance checks
- Procurement and material forecasting
Real Estate
Support for property management, marketing and valuation.
- Property listings and search
- Real estate queries
- Tenant communication
Tech Start-ups
Automated customer interactions and better engagement for growing products.
- User onboarding
- Product recommendations
- Customer support assistants
- User behaviour analytics
Media
Automated content delivery and audience interaction.
- News and media chatbots
- Content recommendations
- Sentiment analysis
Oil and Gas
Chatbot automation for operations and maintenance.
- Safety compliance monitoring
- Logistics coordination
- Equipment maintenance
- Resource tracking
Space
Conversational access to satellite and mission data.
- Satellite data analysis
- Mission diagnostics
- Anomaly detection in space systems
NGOs and Non-profits
Automation for social impact, fundraising and policy research.
- Donor engagement and fundraising
- Grant applications and reports
- Community outreach
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.
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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 does AI chatbot development involve?
Designing, training and deploying conversational AI models that interact with users, automate tasks and connect to your business systems. It covers the architecture, the language models, the data used to train them and the integration into your workflows.
How do you run a chatbot project?
In five stages. Discovery: we analyse your needs, define goals and assess feasibility. Initial setup: we prepare your data and select the models. MVP: we test the chatbot's capabilities and refine it on feedback. Scaling and integration: once validated, we integrate it into your workflows. Evaluation: we monitor performance and fine-tune the models.
Can the chatbot connect to our CRM or ERP?
Yes. We integrate chatbots with CRM, ERP and other business systems, so the bot can act on the data and processes you already run instead of working as a separate tool.
How do you handle security and compliance?
We implement security measures that protect the chatbot against vulnerabilities and support compliance with data protection regulations, and we apply ethical AI frameworks for responsible and fair interactions.
Which technologies do you use?
We work with frameworks including GPT-based models, BERT and Dialogflow, as well as custom machine learning models, chosen according to your use case.
How long does chatbot development take?
It depends on complexity, customisation and data availability, typically from a few weeks to several months. The MVP stage lets you validate the chatbot before committing to full integration.
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