AI business applications – process, learn and act upon any external data

Although artificial intelligence is not a new phenomenon, the accessibility of large language models and text generators to the general public over the past year has given this technological area a significant boost in both attention and expectations, fueled by Big Tech's bold promises of an AI revolution.

We, too, see enormous potential in AI and cognitive technologies. However, we are aware that AI can only deliver on its promises if it is implemented based on a concrete and well-thought-out strategy. As with any digital transformation, AI-driven changes for most companies must occur in small steps, through the realization of specific and value-focused use cases.

Kruso offers a palette of specialized AI transformation services that can be bundled and tailored to match the organizational maturity, time to market and strategy of your business.

We have delivered AI solutions for organizations like:

Application areas & our services:

AI strategy

The complex statistical and transformer models used in AI solutions is a Black Box for most people, making it difficult for companies with AI aspirations to learn from first-mover companies like OpenAI, Google, and Tesla. We can open the box for your company and help draw concrete parallels between your core business and the current/emerging AI technology landscape.

 AI maturity assessment

We asses your company’s current readiness and maturity in the field of artificial intelligence (AI). The goal is to identify current strengths, weaknesses, opportunities, and threats related to AI, so your company can develop a clear strategy for AI implementation that fits your needs and business objectives.

AI use case

Like any other technology, an AI-based business initiative can only create value if it’s rooted in specific use cases and realistic business goals. We can facilitate a clarification process that establishes your company's AI-transformed vision through, for example, Business Capability Mapping and AS-IS vs. TO-BE exercises, aligning thought leaders and experts within your company on an AI-driven future and how to take the first steps towards it.

Skive MunicipalityAI implementation

AI feasibility study and proof of concept (POC)

Many companies are — rightfully — conservative regarding how experimental and exploratory one can be in development projects with new technologies like AI. With a feasibility study and POC, we can bridge the gap between your theoretical case and real-world technological implementation. We design and test user experiences and AI components on a small scale through an agile cross-disciplinary sprint. We summarize the results into a TO-BE interaction prototype and system architecture, providing your company with concrete data and certainty that the vision can be realized before making a large investment!

User experience and usability in an AI paradigm

Cognitive technologies, deep learning, and large language models can shift the usability genre to focus more on how the machine can understand the human, rather than the traditional UX where the focus is the opposite. This requires smart application of a new toolbox in design projects to design concepts based more on common statements/prompts than traditional navigation hierarchies. We are ready to bring true human-centric design for your users!

Ecosystems and data

Effective AI solutions know both your organization and your users, delivering personalized, precise answers and results. This requires content and integration with your data. We identify data needs and opportunities and facilitate the integration of internal and external source systems, giving the solution the best chances for success.

Training AI models

The full benefit of generative AI models, in particular, is realized over time and is the result of various training efforts. Use cases are therefore flexible and can be continually matured and expanded as the model develops. We facilitate the necessary AI model training activities based on the current maturity stage and specific improvement goals, including:

Supervised, unsupervised, and reinforcement learning
Advanced model training with deep learning
Transfer learning and fine-tuning of pre-trained models
Data preparation and feature engineering
Hyperparameter tuning and model optimization

AmuseRe-defining digital strategy

Implementation of AI-based business applications

Once the strategic foundation, business case, and organizational alignment are in place, we can assist in the technological implementation of your company's AI project. We can either provide AI architects to support your internal development team, or we can enter into an A-Z project agreement, providing a full project team.