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AI Platforms
& Model Integrations
We work with leading AI providers and models, selecting the right technology based on the use case, data sensitivity, and cost structure:
What We Build With AI
We design and implement AI features that are directly connected to product logic and user workflows, including:
Voice and multimodal AI integrations
Text analysis, summarisation, and classification
Multilingual AI features
Intelligent search across internal data
Document-based Q&A systems (RAG)
AI assistants and chat interfaces
AI Integration Into Existing Systems
Our solutions are designed to work reliably in production environments, with proper logging, monitoring, and fallback mechanisms.
Internal tools and admin dashboards
Backend services and APIs
Web and mobile applications
AI rarely works as a standalone component. We integrate AI directly into:
Security, Control & Cost Management
We build AI systems with control and predictability in mind:
Usage tracking and cost optimisation
Usage tracking and cost optimisation
Prompt and output governance
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Data access control and isolation
Typical Use Cases
Decision support and analytics
Workflow automation and operational support
Customer-facing AI features
Deliver real-time dashboards and predictive models that turn data into actionable strategies.
Streamline repetitive tasks like data entry, approvals, and reporting to free up your team for high-value work.
Create chatbots, recommenders, and personalized experiences that boost engagement and satisfaction on your platforms.
Build intelligent search tools that instantly retrieve insights from vast document libraries, saving hours on research.
Internal knowledge bases and document assistants
Our AI development services are commonly used for:
Related Projects
Related Projects
QA FOR FINTECH
Automated regression testing that cut release cycles and gave the team real confidence in every deploy
AI Assistant
An assistant that searches Gmail and Drive, pulls the right context, and drafts replies — with a human always in the loop
EcoPlant web app
A web app for managing tree inspections, risk levels, and compliance exports — all in one place.
Related Services
FAQ – AI Development
Yes. We design AI systems that work only with your internal documents and data sources, using controlled retrieval mechanisms.
Not necessarily. Chainweb Group offers both cloud-based AI integrations and self-hosted or private model deployments. For cloud providers such as OpenAI or Anthropic, enterprise data handling agreements are applied. For projects with strict data residency requirements, we deploy models on your own infrastructure — your data never leaves your environment.
A focused AI integration — for example, adding an AI assistant to an existing internal tool or CRM — typically takes 3 to 6 weeks at Chainweb Group. More complex systems involving custom knowledge bases, multi-model pipelines, or real-time data feeds take 8 to 16 weeks. Scope is defined and agreed before work begins.
At Chainweb Group, focused AI integrations start from approximately €8,000–€15,000, depending on the scope and number of systems involved. Standalone AI products or multi-model platforms with custom training pipelines start from €25,000. We recommend a discovery call to produce a realistic estimate before any commitment.
- Yes — when properly designed. We build AI systems with monitoring, fallback logic, and clear limitations.
We implement usage monitoring, model selection strategies, and optimisation techniques to keep costs predictable.
Yes. AI systems require ongoing attention: models are updated by their providers, prompts drift in performance over time, and usage patterns change. Chainweb Group offers post-launch monitoring, prompt maintenance, model version updates, and performance optimisation as part of a support agreement.
Yes. The majority of AI projects delivered by Chainweb Group are integrations into existing systems, not greenfield builds. We connect AI capabilities to your current stack through APIs, webhooks, or purpose-built middleware layers. No full rewrite is required in most cases.
Chainweb Group builds fallback mechanisms into every AI system so that errors do not cause product failures. Outputs are logged, monitored, and — where required — routed through a human review step before any action is taken. Confidence thresholds are configured so the system escalates low-certainty cases rather than guessing. This is sometimes called a 'human-in-the-loop' architecture.
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Service
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Interface design
Security
Management
Development
Budget in EUR
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10K–50K
more than 50K
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