This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.
AI - SMART BUSINESS SOLUTIONS
The application of AI uses intelligent applications to solve classification, prediction and control problems, automating, aggregating or improving real-world business use cases.
As AI technologies advance rapidly, enterprise adoption continues to grow across industry use cases:
- Manufacture
- Banking, Fintechs and Insurance
- Marketing
- Telco
- Retail
- CPG&B
- Manufacture
- FM Logistics & Transportation
Benefits
The commitment to innovation and process begins with Teippo as the expert partner in establishing clear objectives and organizing the company’s internal data. Below are our 5 key requirements for a data-driven business strategy that we developed together with them:
- Cost savings: Up to 90% of respondents mentioned cost reduction in 2022
- Global revenue growth: Through the end of 2021, 75% of companies that adopted lean models saw revenue growth in that year, according to a McKinsey survey
- New use cases: Automation and obtaining accurate information through new use cases will unlock additional capabilities and business opportunities
- Greater accessibility to optimized AI models and easier implementation: Thanks to new technologies and practices, such as machine learning operations and software automation, AI should be more accessible and easier to implement
Some of the advantages of using a text analysis service for any use case
Reduction of reading time. Accelerate the next wave of productivity
More efficient search of large volumes of disparate data
Allow employees and users to focus on deeper analysis and more effective queries
Reducing the potential for bias from human summary techniques
(depends on the fairness of the training data)
GCP, AWS and Azure Open AI Services - Chat GPT 3.5/4.0
OpenAI (ChatGPT) + Cognitive Search is an AI-powered platform as a service (PaaS) in the cloud that will help our customers build intelligent, interactive and rich search experiences for documents and images. It is available on AWS, GCP and Azure.
Created from any information source or knowledge base, such as files, text, emails, PDFs, images, videos, voice messages and structured or unstructured data, our platform allows searches and presents results on various platforms or interfaces of user, both for employees and clients. This allows interactive natural language processing experiences to be integrated into information search.
Teippo works closely with its clients to create and leverage this service to develop market-leading intelligent content applications, providing transformation and innovation in the way they offer their services.
Advantages
Some of the advantages of using a summary service for any use case are:
- Reduction of reading time
- More efficient search of large volumes of disparate data
- Reducing the risk of bias in human summarization techniques is an important benefit, provided there is unbiased training and fair training data.
- Allow employees and users to focus on deeper analysis and more effective queries
Teippo models power interactive chat capabilities and capture text meaning for search, content moderation, and intent recognition.
Semantic search provides powerful semantic search capabilities that find text, documents, and articles based on meaning, not just keywords.
Open AI (ChatGPT) + Cognitive Search is a platform as a service (PaaS on AWS, CGP and Azure) powered by Articfical Intelligence in the cloud that will help our customers build intelligent, interactive and rich search experiences for documents and images.
Created from any source of information or knowledge base (files, texts, emails, PDF, images, videos, voice messages, structured or unstructured data), it can be searched and presented on different platforms or UIs for employees and clients, to integrate intelligent language processing search experiences interactively.
TEIPPO helps its customers create and use this service to develop intelligent content applications, we offer high-performance multilingual search capability to help businesses scale globally. With cutting-edge as-a-service (PaaS/SaaS) models that will transform and innovate the way you present your products and services.
Analytical Optimization Strategy
- Our strategy is based on data, models, decisions and value, with an emphasis on decision making
- Project development with multidisciplinary capabilities in Teippo: analytics consultants and translators with business experience, data scientists and information integrators
- We develop our models based on a deep understanding of the business opportunity and the processes that will use these models.
- Extensive experience in industries and models allows us, on the one hand, to accelerate the development of solutions as well as provide proven ideas to our clients.
- We offer the "as a service" modeling option, making available to our clients the systems infrastructure and the most modern analytics platforms (private, multi-cloud and public clouds).
- We accompany the implementation of models in business processes
Business vision and strategy
Adoption Transformation Innovation
DATA
MODELS
DECISIONS
VALUE
Typical AI and Advanced Analytics Capabilities Challenges
- Understanding and Adoption: Connect new ideas for improvement, data governance with a company's key strategic and analytical processes of performance (KPI) and the quantification of the benefits that can be obtained from predicting, measuring or improving the use of data
- Data curation strategy: understanding the context of the data, guaranteeing its quality and adaptation to the processes
- Algorithm selection: mathematical, statistical and probabilistic methods and structures
- Hypothesis testing and use cases: creation and definition of the base model
- Machine learning: Model production, infrastructure establishment, cadences, data science organization
- Model optimization (Model refinement): Quality feedback loop (concept drift/volatility change)
- Measurement: Precision targets, KQI, KPI, KRI, reference measurements