Top Generative AI Development Company

Generative AI is an artificial intelligence technology, to be more precise, deep learning models that are trained on various datasets to generate statistically probable outputs in the form of text, audio, visuals, etc., as per input prompts.

Our AI developers follow ethical guidelines, make algorithms transparent, and conduct regular security audits. They anonymize and de-identify data, address biases, and obtain user consent transparently. Our team follows strict security protocols and AI development best practices and integrates industry-specific compliances to create fair systems, ensuring the responsible and ethical use of artificial intelligence.

Yes, of course! At MindInventory, our team is confident about their experience in working with diverse AI development projects and delivering generative AI software development solutions, such as AI forecasting solutions for supply chain, AI-powered chatbots like Replika, AI-powered Fintech solutions, test case automation solutions, online proactive assessment evaluator, IT project lifecycle automation and supervision, and many other custom generative AI solutions. Share your requirements with us today!

Developing Generative AI solutions is quite a time-intensive process as it requires tons of effort in building mathematical and statistical models, data gathering and pre-processing, customizing LLMs and third-party generative AI models and architectures, training foundation models, and a lot more. So, these processes, including the expertise of AI/ML developers and data scientists, act as factors affecting the time for this project.

Yes, we do provide post-deployment support, which includes timely bug fixes, system optimization, and keeping the Generative AI solution up-to-date according to the latest technology trends. To avail of this dedicated post-deployment support, you don’t need to hire a full-time programmer - instead, you can opt for our flexible bucket model that allows you to buy fixed hours, which you can utilize when and as needed.

The process to start your Generative AI development and integration project with MindInventory is very simple. All you need to do is fill out the Contact Us form. You can also directly email us or message us on Skype with your requirements and project-related references or documents, if available, for quick assistance to get started with MindInventory.

The technology stack for Generative AI development can vary based on specific project requirements and preferences. However, a typical stack may include:

• Deep Learning Frameworks: pytorch, tensorflow
• Modules/Toolkits: Python, SQL, MongoDB, ChromaDB, Pinecone, Neo4j
• Generative AI Models: GAN, Diffusion, LLM
• Neural Networks: CNN, Transformers
• Libraries: Numpy, Pandas, OpenCV, Langchain, LlamaIndex, FastAPI
• Cloud Platform: AWS Cloud, Microsoft Azure, Google Cloud Platform

Considering security and ethical AI development best practices, our Generative AI software development team starts with first understanding your problem statement, creating a system for data gathering, preprocessing, integrating Embeddings for generation and chunking (if using RAG pipeline), creating Vector database storage (if using RAG pipeline), work on data retrieval methods, context awareness by passing entire data to make LLM learn about data and what to provide when asked such questions, testing and validation of implemented models, deployment and integration, and further work on proactive monitoring and maintenance of the system.Please note that this Generative AI development approach may change according to your project requirements.

Yes, we can! We have come across a couple of clients who previously were working with some other technology partners, but due to some reasons, their mission-critical app development was left unfinished. And we understand the importance of bringing your app ideas to life as soon as possible. Please schedule a call with us; our experts would love to discuss your ideas, find the right-fit solution, and actualize it.

We ensure that the clients’ intellectual properties are kept protected all the time, from closing the deal with an NDA and keeping the code secure in the private Git to delivering the project with all formalities, code ownership, copyrights, etc.