THE FUTURE OF FINDING THINGS
Semantic search takes finding what your customers are looking for to a whole new level. This technology understands the meaning and context of search queries, rather than just relying on exact keyword matches.
AI Semantic Search
Semantic search takes finding what your customers are looking for to a whole new level. This technology understands the meaning and context of search queries, rather than just relying on exact keyword matches. By using Natural Language Processing (NLP) and machine learning, semantic search engines can recognize the meaning behind a query and deliver relevant results, even if the entered terms don't exactly match the stored data.
Give users exactly what they are looking for. And more.
Why Semantic Search?
- 100% Improved Search Results: Delivers significantly more accurate results, enhancing user satisfaction.
- +30% Order Value: Boosts order value by effectively matching products to user search query.
- Better User Experience: Users enjoy a smoother, more intuitive search experience.
- Less Manual Work: Reduces the need for manual keyword/ synonyms updates and maintenance.
- Fast Time-to-Market: Ready-to-use frameworks and tools accelerate go-live.
What we do
Using industry-specific data and queries, we evaluate transformer models, which are deep learning models designed to understand context and meaning.
We prepare industry-specific training datasets and, just like a musical instrument, we fine-tune the selected model. We iterate and optimize hyperparameters , who control the learning process and influence the model parameters that the algorithm ultimately learns.
Finally, we weave the fine-tuned model into the fabric of search infrastructure and applications. Additionally, we tailor results to our customers’ individual needs, continuously monitor performance, and keep the model updated.
Semantic Search vs. Keyword Search
Semantic Search focuses on understanding the meaning and context behind a query. It uses natural language processing to interpret the meaning behind words, providing results that align with what the user is truly seeking. This approach considers synonyms, related concepts, and the overall context to deliver more relevant outcomes, without the need for manual synonym lists.
Keyword Search operates on a more straightforward level, matching the exact words in a query to those in a database. It doesn't account for context or meaning, focusing solely on literal word matches. That’s why it can miss the mark if the exact terms aren't present, often leading to less relevant results and manual work in form of constant updates to keyword and synonym lists.
Better Search in No Time
Implementing AI-powered semantic search can be achieved in hours rather than months, thanks to advanced pre-trained models and cloud-based solutions. These tools offer ready-to-use frameworks that streamline the integration process, eliminating the need for extensive custom development. By leveraging APIs and scalable infrastructure, businesses can quickly deploy semantic search capabilities with us, enabling them to understand user inquiries and deliver relevant results with minimal setup time.
What sets us apart
Delivering is our top priority. Through smart management, we keep projects on track from discovery to go-live and beyond.
Our experience allows us to quickly grasp the necessary context and then take responsibility for specific domains or even overall coordination.
Our tech experts work on complex architectures and maintain solutions at the highest level, always ready for the next upgrade.
Benefiting from our partner ecosystem, we are able to model the right technology stack for every use case.
We work in partnership and integrate seamlessly into project teams, developing suitable solutions with openness and pragmatism.
Ready for more?
Let's talk ideas, challenges, needs, and solutions.
Daniel Ristig
Director New Business & Strategic Partnerships
daniel.ristig@turbinekreuzberg.com
+49 160 78 6464 7