Pushing boundaries with smart Large language models
Large Language Model Development and Consulting
Analyse and extract meaningful insights from your data, get data-driven recommendations to optimise your processes, and reduce operational costs by automating your workflows with our expertise in large language model (LLM) development.
15+
Years
expertise
140+
Satisfied
clients
120+
Team
members
Our services
LLM development
We create tailored LLMs using foundational models, such as ChatGPT, Gemini, Llama, Claude, Mistral and smoothly integrate them into your ecosystem. Our NLP, machine learning, and data science experts check for performance, and ensure the LLM model is fully prepared to give an accurate result for a specific task.
- User workflow design
- Dataset preparation
- Integration of existing cloud-based AI solutions from AWS, Azure, OpenAI
- Integration of LLM into your systems
Consulting services
We assist in refining your business vision and outline a complex strategy for implementing language models. Our specialists identify use cases, evaluate your proprietary data, and offer actionable advice on technological infrastructure.
- Business case analysis
- Proof of Concept development
- Proprietary data overview
- Project roadmap development
Fine-tuning services
We enhance off-the-shelf LLMs by fine-tuning them with your data, maximising the base models’ value for your business. Our machine learning engineers refine model accuracy and efficiency to meet your unique operational needs.
- Fine-tuning of large language models
- API integration
- Modernisation of data architecture
- Automation of large language models
Continuous support and optimisation
Our team ensures the optimal performance of your language learning models round the clock. Our generative AI solutions evolve alongside your business needs, from continuous optimisation to troubleshooting.
- Model monitoring and management
- Regular model updates
- Data retraining processes
- Risk management and compliance assurance
Altamira is trusted by
Our expertise
Natural Language Processing
We develop NLP models using structured and semi-structured data and libraries such as TensorFlow, Keras, PyTorch. Our solutions enable information extraction from diverse sources, including search queries, internet data, business databases, and audio files.
Few-shot Learning
Our machine learning models excel through few-shot learning when acquiring labelled data, which is often challenging and costly. This approach allows models to generalise from minimal labelled examples during training, optimising performance with limited data inputs.
Machine Learning
Our developers use adaptable ML toolkits (TensorFlow, Keras, PyTorch) to build sophisticated ML solutions. These tools empower us to implement diverse algorithms, including supervised, unsupervised, and reinforcement learning methods.
In-Context Learning
In-context learning enriches language models by integrating contextual information during training. This technique enhances models’ ability to comprehend context, enabling advanced reasoning, inference, and specialised problem-solving capabilities.
Sentiment Analysis
We employ sentiment analysis to determine the emotional tone (positive, neutral, or negative) of textual data. Thus, your business can refine products and services based on customer feedback and sentiment insights.
Use cases of LLM solutions
01 Content generation and automation
02 Customer support
03 Data analysis
04 Personalisation in recommendations
05 Virtual assistants
06 Language translation
LLMs automate content creation across domains such as journalism, marketing, and entertainment by generating human-like text based on input prompts. They streamline workflows by reducing manual effort in content production and AI text analysis.
Integrating LLMs into chatbots and virtual assistants enhances customer support interactions. These models contextually understand and respond to customer queries, improving the overall customer experience.
LLMs analyse large datasets to extract meaningful insights and trends. They assist businesses in making data-driven decisions by processing unstructured data from sources like social media, customer reviews, and research papers.
LLMs power recommendation systems by understanding user preferences and behaviour from text inputs. They optimise personalised content delivery in eCommerce, streaming platforms, and social media.
AI-powered virtual assistants automate customer interactions, provide personalised service, assist with troubleshooting, answer inquiries 24/7, and guide customers through the sales process. By streamlining interactions and delivering customer-centric support, they elevate customer satisfaction levels.
LLMs automate language translation, enabling businesses to confidently overcome language barriers and expand their global footprint. These models ensure flawless and precise translations, facilitating smooth cross-cultural communications. Businesses can offer real-time written and spoken translations for live chats, international events, and customer support interactions, enhancing global connectivity.
Benefits of Large Language Learning models
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Our cooperation models
Dedicated development team
We offer a dedicated software development team with niche expertise tailored to your project requirements. Our team is committed to delivering exceptional results and ensuring your project's success.
Team extension
Augment your existing teams with the specific skills and knowledge needed for your projects. We ensure smooth integration and collaboration between our experts and your in-house team to help you scale the development.
Project-based model
We offer a project-based engagement model for clients with well-defined project objectives and timelines. Our experts work closely with you to understand your project requirements and deliver results that align with your goals.
Why Altamira
- 20+ AI engineers offering a wealth of knowledge and experience.
- Numerous successfully completed AI projects
- Extended partnerships with an average cooperation duration of 12 months
- Flexible engagement models tailored to suit your specific project needs
- Compliance with all necessary security standards, ensuring the confidentiality and integrity of your data.
- Full support throughout every stage of your project, from initial conception to final implementation
Discover why customers choose Altamira
The team was receptive to feedback, adapting resources to ensure effective collaboration.
CTO, SOLJETS
Ryan Crawford
I am absolutely satisfied with how my app looks and functions. It is exactly what I wanted to get when I decided to go with this team.
CEO & Co-founder, Aquiline Drones
Barry Alexander
CTO, Ticker Tocker
Jonathan Kopnic
Their holistic approach was evident in how professionally they integrated our ideas with their expertise, resulting in a product that totally meets our goals.
CEO, Elula
Deveren Fogle
CEO, CTRL Golf
Ian Cash
Head of Services, Universal Edition
Andreas Bintinger
People also asked
NLP, or Natural Language Processing, is a field of artificial intelligence focused on the interaction between computers and human language. It involves tasks like language translation, sentiment analysis, and text summarisation. LLM, or Large Language Model, is a type of AI model that has been trained on vast amounts of text data to understand and generate human-like text. While NLP covers a wide range of techniques and applications, an LLM is a specific tool used within NLP to perform complex language-related tasks. Get in touch to learn more.
Yes, an LLM is a type of neural network. Specifically, it is a deep learning model that uses layers of neurons to process and generate human language. These models are typically based on architectures like transformers, which allow them to handle and generate coherent and contextually relevant text based on the data they have been trained on. Get in touch to learn more.
An LLM is a broad type of AI model designed to understand and generate text across a wide range of contexts and topics. A chat model, on the other hand, is a specialised application of an LLM tailored for conversational interactions. While both use similar underlying technology, chat models are fine-tuned to handle dialogue, maintain context over a conversation, and provide responses that mimic natural human conversation. Contact us to get a free expert consultation.
An example of an LLM model is OpenAI’s GPT-4. This model has been trained on a diverse dataset containing a wide range of internet text, enabling it to perform various language tasks such as text generation, translation, summarisation, and answering questions.
An LLM is useful for a variety of applications, including but not limited to:
- generating human-like text for chatbots
- virtual assistants
- translating languages
- summarising long documents
- answering questions
- content creation
- sentiment analysis
- improving search engine results.
Its ability to understand and generate text makes it a powerful tool for enhancing communication and automating language-related tasks. Contact us to get a free expert consultation.
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