Results that speak

Examples of how we have helped our clients achieve their goals with AI and modern technology.

70% fewer support tickets

AI-driven customer service

E-commerce

90% time saved

Automated document handling

Finance & insurance

40% less downtime

Predictive maintenance

Manufacturing

E-commerce70% fewer support tickets

AI-driven customer service

We built an intelligent chatbot with RAG architecture for e-commerce that automatically answers common questions.

Challenge

The client handled over 2,000 support tickets per month, the majority being repetitive questions about delivery times, returns, and product information. The support team was overloaded and response times were increasing.

Solution

We developed an AI-driven customer service solution based on RAG architecture (Retrieval-Augmented Generation) that connects to the client's product catalog, order data, and FAQ database in real time. The chatbot understands natural language in Swedish and English and can handle complex queries requiring information from multiple sources.

Results

Within three months of launch, support tickets decreased by 70%. Customer satisfaction increased by 25% thanks to faster response times around the clock. The support team could focus on complex cases requiring human contact.

Technology

PythonLangChainOpenAI GPT-4PostgreSQLNext.jsVercel

Finance & insurance90% time saved

Automated document handling

AI-based data extraction and categorization that drastically reduced manual processing.

Challenge

An insurance company processed thousands of claims manually every week. Handlers spent most of their time reading, categorizing, and extracting data from incoming documents — a time-consuming and error-prone task.

Solution

We built an AI pipeline that automatically reads incoming documents (PDF, email, images), extracts relevant information using NLP and OCR, categorizes cases by type and severity, and populates the handler's system automatically. The system continuously learns from handlers' corrections.

Results

Processing time per case decreased by 90%. Error rates dropped by 60% compared to manual handling. The company could reallocate resources to more qualified work and significantly improved their customer experience.

Technology

PythonTesseract OCRspaCyFastAPIAzure Cognitive ServicesReact

Manufacturing40% less downtime

Predictive maintenance

ML models that predict equipment failures before they happen in industrial settings.

Challenge

A manufacturing company suffered from unplanned downtime costing millions in lost production. Existing maintenance was scheduled — not based on actual machine data — leading to both over-maintenance and unexpected breakdowns.

Solution

We installed sensors on critical equipment and built ML models that analyze vibrations, temperature, and energy consumption in real time. The system identifies patterns that precede failures and alerts the maintenance team before problems occur. A dashboard provides full visibility into the machine fleet's status.

Results

Unplanned downtime decreased by 40% during the first six months. Maintenance costs dropped by 25% by avoiding unnecessary service intervals. ROI was achieved within six months of launch.

Technology

Pythonscikit-learnTensorFlowInfluxDBGrafanaNode.jsMQTT

How we work

Every project starts with a deep understanding of the client's business. We identify where technology creates the most value, build a solution that fits, and ensure it works in practice — not just on paper.

Discovery

We analyze your processes and identify where AI and automation deliver the greatest impact.

Development

Iterative development with frequent check-ins — you're involved every step of the way.

Delivery & operations

We deliver a complete solution and ensure it works in your day-to-day operations.

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