Our Adaptive AI Development Services
Consulting and Strategy Development
We assess your business goals and requirements to identify the potential of AI in your business and build a roadmap for AI implementation that outlines the strategies to solve your most challenging business problems with AI.
Maintenance and Upgrade
Leverage our ongoing support and maintenance services to fix any issues or bugs and enhance system performance. Our AI engineers will also upgrade the deployed adaptive AI-based solution with additive features to meet your evolving business requirements.
Custom Adaptive AI Model-based Solutions Development
We build custom adaptive AI solutions that use advanced machine learning techniques like transfer and online learning for continual learning of the AI model used. Whether a predictive analytics solution or an AI-powered chatbot, we create solutions that deliver real-time feedback to users.
Model Integration and Deployment
Enhance your existing applications with real-time data compatibility by integrating adaptive AI models and solutions like virtual assistants and chatbots. This ensures personalized user experiences and highly automated business processes.
From acquiring and modifying to loading the data, our adaptive AI developers efficiently process large amounts of high-quality data utilizing advanced data engineering technologies such as NoSQL, Apache Spark, and Hadoop while maintaining scalability, privacy, and security.
Our Technical Expertise in Adaptive AI Development
Our developers have extensive knowledge of machine learning techniques, including continual, supervised and unsupervised learning, deep reinforcement learning, and attention mechanisms, enabling seamless integration of adaptive AI models into existing systems.
Natural Language Processing (NLP)
Our team of adaptive AI experts can incorporate Natural Language Processing (NLP) into your application for efficient sentiment analysis, text processing, and named entity recognition. NLP can also be utilized for developing chatbots and virtual assistants.
Skilled in using cloud computing technologies, like Microsoft Azure, Google Cloud Platform (GCP), and Amazon Web Services (AWS), that provide access to large data sets, our developers can safely deploy and scale your adaptive AI solutions.
Our developers have expertise in deep learning algorithms and their underlying neural networks like RNNs, CNNs, and long short-term memory (LSTM) networks that help adaptive AI models to learn data and make predictions automatically.
With expertise in utilizing top-notch tools, frameworks and libraries like TensorFlow or PyTorch, our team develops robust computer vision algorithms and techniques, including image classification, object detection, segmentation and scene understanding.
Our developers have expertise in developing adaptive AI-based solutions that use predictive analytics algorithms and techniques, including random forests, decision trees and gradient boosting, facilitating businesses to make data-driven decisions based on real-time data.
Our Adaptive AI Systems Development Process
Identify the Problem
The first step in developing an adaptive AI solution is to identify the problem you want to solve. This involves understanding the business need or user requirement that the AI will address, as well as any constraints or limitations on the solution.
Once you’ve identified the problem, you need to gather relevant data to train your AI model. This may involve collecting data from a variety of sources, including internal company data, public datasets, and user-generated content.
Clean and Preprocess Data
After you’ve gathered your data, you need to clean and preprocess it to ensure that it’s suitable for training your AI model. This involves removing duplicates, handling missing values, and transforming the data into a format that can be used by your model.
Validate and Test the Model
Once your model is trained, you need to validate and test it to ensure that it’s performing as expected. This involves evaluating the model’s accuracy, precision, recall, and other performance metrics, and making any necessary adjustments to improve its performance.
Develop and Train the Model
With your data cleaned and preprocessed, you can begin to develop your AI model. This involves selecting an appropriate algorithm or approach, tuning hyperparameters, and training the model on your data.
Deploy the Model
Once your model has been validated and tested, you can deploy it in a production environment. This may involve integrating the model with other systems, such as a web or mobile app, and setting up infrastructure to support the model’s ongoing operation.
Monitor and Update the Model
After your model has been deployed, you need to monitor its performance to ensure that it’s continuing to perform as expected. This may involve setting up monitoring and alerting systems and periodically updating the model to improve its performance based on new data or user feedback.
AI Models We Have Expertise in
A set of OpenAI models capable of performing natural language processing tasks such as text generation, summarization, translation and question answering.
A set of OpenAI models, including the highly capable and cost-effective Gpt-3.5-turbo, that improve on GPT-3 and can generate text or code.
A set of OpenAI models that can solve complex problems with high accuracy, thanks to its advanced reasoning capabilities and broader general knowledge.
DALL·E by OpenAI generates realistic images and artwork based on text prompts. It can produce images of a specified size, modify pre-existing images and generate variations of user-provided images.
Whisper is a general-purpose speech recognition OpenAI model that can perform language identification, speech translation and multilingual speech recognition.
OpenAI's Embeddings are numerical representations of linguistic units like words and phrases that capture the semantic meaning and relationships between them.
Moderation models are machine learning OpenAI models designed to assist in content moderation tasks, such as identifying and removing inappropriate or harmful content from online platforms.
Stable Diffusion generates detailed images from text prompts and can also be used for tasks like inpainting, outpainting, and image-to-image translations guided by text.
Midjourney is an AI-powered image generator that creates images in response to textual prompts. The images produced by Midjourney feature a distinct artistic flair.
Google's Bard, powered by LaMDA, is a text-to-text generative AI chatbot designed to generate human-like responses to natural language prompts, making it capable of engaging in conversations with humans.
LLaMA (Large Language Model Meta AI) is a foundational large language model designed to generate text, have conversations, summarize written material, solve math theorems or predict protein structures.
Claude is a large language model (LLM) by Anthropic, trained as a virtual assistant that can be integrated with business workflows. Claude, accessible through both a chat interface and API in Anthropic’s developer console, can perform an extensive range of conversational and text-processing tasks.
Our Adaptive AI-based Development Services Cater to a Wide Array of Industries
Banking and Finance
Supply Chain and Logistics
Our Engagement Models
Dedicated Development Team
Our blockchain developers are hands-on the cognitive technologies to deliver high-quality services and solutions to clients.
Our team extension model is intended to help clients who want to extend their team with the right expertise required for their project.
Our project-based model and software development specialists are there for customer collaboration and specific client project engagement.
Get Started Today
1. Contact Us
Fill out the contact form protected by NDA, book a calendar and schedule a Zoom Meeting with our experts.
2. Get a Consultation
Get on a call with our team to know the feasibility of your project idea.
3. Get a Cost Estimate
Based on the project requirements, we share a project proposal with budget and timeline estimates.
4. Project Kickoff
Once the project is signed, we bring together a team from a range of disciplines to kick start your project.