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Comprehensive LLM Development and Consulting Services
End-to-end LLM Services for AI Excellence
Get comprehensive services from LLM consulting to LLM support and maintenance with Hidden Brains. We can create a robust platform that meets all your needs.
Prompt Engineering
Our AI development company designs and optimizes workable prompts for the performance optimization of large language models. This gives the desired output for specific use cases and your custom business needs.
LLMOps Services
We streamline the deployment, tracking, and management of large language models. It allows proper functioning and optimization. Our services include training the models for improved efficiency and scalability.
Fine-tuning LLMs
Our specialization lies in fine-tuning large language models for unique datasets through prompt engineering. We pick pre-trained models and train them for specific datasets to improve performance.
LLM Integration
We effortlessly incorporate powerful pre-trained models like GPT-4 and BERT into your app. We have expertise in architecture understanding, constant training and retraining, and domain customization.
LLM Customization
Our LLM customization service allows businesses to tailor their large language models to specific needs. It improves performance for content generation, data analysis, and customer support tasks.
LLM Support & Maintenance
Our expert LLM support and maintenance team extends its services to fix issues, monitor performance, and update solutions with new features. We ensure your models remain up-to-date and secure for long-term success.
Our AI development company designs and optimizes workable prompts for the performance optimization of large language models. This gives the desired output for specific use cases and your custom business needs.
We streamline the deployment, tracking, and management of large language models. It allows proper functioning and optimization. Our services include training the models for improved efficiency and scalability.
Our specialization lies in fine-tuning large language models for unique datasets through prompt engineering. We pick pre-trained models and train them for specific datasets to improve performance.
We effortlessly incorporate powerful pre-trained models like GPT-4 and BERT into your app. We have expertise in architecture understanding, constant training and retraining, and domain customization.
Our LLM customization service allows businesses to tailor their large language models to specific needs. It improves performance for content generation, data analysis, and customer support tasks.
Our expert LLM support and maintenance team extends its services to fix issues, monitor performance, and update solutions with new features. We ensure your models remain up-to-date and secure for long-term success.
Our Mastery in LLM Models to Drive AI Innovation
We use our deep knowledge of large language models (LLMs) to help businesses innovate. Our LLM company builds smart, scalable apps that create real impact across various industries.
Chat GPT
Gopher
PaLM
LLaMA
Claude
DALL-E
Meta Llama
BERT
Mistral
Chinchilla
Stable Diffusion
J1-Jumbo
T5
Falcon
Phi 2
Vicuna
bloom-560m
Transformative Solutions with Our LLM Expertise
We have consulted, developed, and deployed LLM solutions for our clients. We helped our clients improve their business and achieve set goals.
- 70%Improved Decision Making
- 50k+Cost Saving
- 60%Planning Efficiency+
How do We Make Our LLMs Work?
A simple three-step process. Our LLM solution can perform intelligent tasks from raw data. We can do this for your business as well. Check out how:
Step 1 – Feed the Intelligence
We feed different data types like text, images, code, audio, and structured data into the system to train it in a real-world context.
Step 2 – Process with Precision
LLMs like GPT, BERT, and Claude analyze the input. They identify patterns and context for meaningful interpretation.
Step 3 – Activate Real-World Outcomes
The model performs multiple tasks. It includes translation, summarization, classification, code generation, and chatbot responses tailored to your needs.
Step 1 – Feed the Intelligence
We feed different data types like text, images, code, audio, and structured data into the system to train it in a real-world context.
Step 2 – Process with Precision
LLMs like GPT, BERT, and Claude analyze the input. They identify patterns and context for meaningful interpretation.
Step 3 – Activate Real-World Outcomes
The model performs multiple tasks. It includes translation, summarization, classification, code generation, and chatbot responses tailored to your needs.
Advanced Technologies Powering Our LLM Solutions
Being one of the leading LLM companies, Hidden Brains uses the latest technologies and tools. We build future-ready solutions with modern-day tools.
PyTorch
Keras
Caffe2
TensorFlow
TensorLite
Docker
Kubernetes
Microsoft Azure
JavaScript
Google Cloud
IBM Cloud
Oracle
MySQL
Pandas
LangChain
Top LLM Development Model and Training Process
Hidden Brains experts streamline LLM operations to fine-tune LLMs to meet business goals. We open new possibilities with our model consulting services.
Determining Requirements
- Business Audit: Conduct an in-depth audit to define business goals.
- Issue Analysis: Identify and analyze existing challenges that can be solved with LLM consulting.
- Technology Assessment: Evaluate the current technological infrastructure to ensure compatibility.
- LLM Consultation: Develop a structured, loop-free strategy for LLM implementation.
- Opportunity Identification: Discover high-value LLM use cases to maximize business impact.
Data Preparation
- Data Collection: Gather relevant datasets from multiple sources to ensure comprehensive coverage.
- Data Cleaning: Remove errors, duplicate entries, and unnecessary information to enhance data quality.
- Data Transformation: Convert raw data into the appropriate format for model training.
- Feature Selection: Identify and implement key features to optimize model performance.
- Data Splitting: Divide the dataset into training, testing, and validation sets for effective model evaluation.
Foundation Model Selection
- Evaluate Model Performance & Size: Analyze the efficiency and scalability of the model.
- Assess Compatibility: Ensure the model aligns with the required language and tasks.
- Data Strategy: Identify necessary datasets for training and updating the model.
- Resource Availability: Determine the available computational resources for model deployment.
- Model Selection: Choose the best foundation model that suits your business needs.
Evaluating LLM APIs
- Prompt Engineering: Customize input prompts to achieve the desired output.
- Fine-Tuning: Optimize model performance with task-specific adjustments.
- Quality Data Utilization: Use high-quality external data to provide relevant contextual information.
- LLM API Integration: Extract and utilize LLM API data for application development.
- Advanced Optimization: Explore methods like instruction tuning and prompt tuning to enhance model efficiency.
Model Evaluation
- Validation Metrics: Analyze the model using dedicated validation metrics.
- A/B Testing: Experiment, evaluate, and measure model performance through A/B testing.
- Quality Assurance Tools: Use modern tools like HumanLoop or HoneyHive to assess model quality.
- Bug Fixing: Identify and resolve existing bugs and issues.
- Scalability Assessment: Ensure the model has room for updates and future scalability.
Deployment and Monitoring
- Model Evaluation: Assess updates to detect faulty content generation.
- API Monitoring: Regularly track API changes to align with evolving business needs.
- Regulatory Compliance: Integrate compliance measures to protect data and prevent misuse.
- Continuous Monitoring: Utilize advanced tools for ongoing performance tracking.
- UX Optimization: Fine-tune launch settings to enhance user experience.
- Business Audit: Conduct an in-depth audit to define business goals.
- Issue Analysis: Identify and analyze existing challenges that can be solved with LLM consulting.
- Technology Assessment: Evaluate the current technological infrastructure to ensure compatibility.
- LLM Consultation: Develop a structured, loop-free strategy for LLM implementation.
- Opportunity Identification: Discover high-value LLM use cases to maximize business impact.
- Data Collection: Gather relevant datasets from multiple sources to ensure comprehensive coverage.
- Data Cleaning: Remove errors, duplicate entries, and unnecessary information to enhance data quality.
- Data Transformation: Convert raw data into the appropriate format for model training.
- Feature Selection: Identify and implement key features to optimize model performance.
- Data Splitting: Divide the dataset into training, testing, and validation sets for effective model evaluation.
- Evaluate Model Performance & Size: Analyze the efficiency and scalability of the model.
- Assess Compatibility: Ensure the model aligns with the required language and tasks.
- Data Strategy: Identify necessary datasets for training and updating the model.
- Resource Availability: Determine the available computational resources for model deployment.
- Model Selection: Choose the best foundation model that suits your business needs.
- Prompt Engineering: Customize input prompts to achieve the desired output.
- Fine-Tuning: Optimize model performance with task-specific adjustments.
- Quality Data Utilization: Use high-quality external data to provide relevant contextual information.
- LLM API Integration: Extract and utilize LLM API data for application development.
- Advanced Optimization: Explore methods like instruction tuning and prompt tuning to enhance model efficiency.
- Validation Metrics: Analyze the model using dedicated validation metrics.
- A/B Testing: Experiment, evaluate, and measure model performance through A/B testing.
- Quality Assurance Tools: Use modern tools like HumanLoop or HoneyHive to assess model quality.
- Bug Fixing: Identify and resolve existing bugs and issues.
- Scalability Assessment: Ensure the model has room for updates and future scalability.
- Model Evaluation: Assess updates to detect faulty content generation.
- API Monitoring: Regularly track API changes to align with evolving business needs.
- Regulatory Compliance: Integrate compliance measures to protect data and prevent misuse.
- Continuous Monitoring: Utilize advanced tools for ongoing performance tracking.
- UX Optimization: Fine-tune launch settings to enhance user experience.
Proof of Our LLM Solutions Success
Our clients share their experiences of working with us. With our expert LLM consulting and development, we help them reach their business goals, drive innovation, and speed up their processes.
It was more than just a vendor-developer transaction.
We gained technically proficient, highly skilled professionals to achieve our goals and add value to our EPacquire solution.
Where dozens fell short, Hidden Brains delivered
What truly set them apart was their genuine care and alignment with our business goals. Over an 8-month collaboration so far, they elevated engineering possibilities, enabling us to showcase transformative solutions to our stakeholders with our solutions.
Throughout the project, communication was seamless and efficient
I want to express my appreciation for the wonderful job and the excellent service that Hidden Brains, did in creating my first ever App ControlBabyGender.
Integrating TensorFlow for Offline Functioning
Team Hidden Brains has worked tremendously and easily integrated a complex functionality into our system. They were good at their job and provided continuous support. They are my partner for all future endeavors.
I want to say thank you very much for all the support
What I have like the most about Hidden Brains is the constant support, the challenges, the pushing, the encouragement, making sure that we are aligned in terms of the deliverables, the business model and how we will go to market.
Partner with Our LLM Company to Drive Success
Hire Hidden Brains as your LLM development partner. We take care of everything from LLM integration strategies to customization. We manage the entire process end-to-end.
Frequently Asked Questions (FAQ’s)
Clear your queries about LLM development services and consulting with our answers. Feel free to get in touch if you have any other questions; our experts will be happy to help.
- Domain-specific Accuracy You can train your custom LLM based on industry-specific data, allowing it to understand relevant data and terminologies.
- Improved Data Handling Custom data can be optimized to process confidential data per business or regulatory requirements. It ensures data security and proper compliance.
- Improved Model Fine-tuning You can fine-tune custom LLM models for specific tasks like legal document review, technical troubleshooting, sentiment analysis, and getting desired results in particular areas.
- Better Integration Custom LLM development makes it easy to connect with your current systems. It works well with tools like ERP and CRM, helping your team run smoother and use data more effectively across the organization.
- Customer support automation with chatbots and virtual assistants
- Data analysis with insight extraction and report generation.
- Code generation
- Language-based app development
- Fine-tuning a pre-trained LLM: 2–6 weeks
- Building a full custom model: 3–6 months or more.
Timelines vary based on dataset size, use case, security needs, and infrastructure setup.
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