Unlock the full potential of AI Innovation with our Artificial Intelligence Development Services

Go beyond exploration and experimentation to execution; accelerate your business operations with generative AI and machine learning development services. We provide pragmatic solutions, customized for domain-specific use cases, to drive meaningful improvements in your business outcomes.

Services

Use case driven innovation for assured success

As a dedicated Artificial intelligence development services company, we help you with integrating AI into existing workflows to enhance decision-making with decision intelligence, improve employee performance and operational efficiency, and uncover actionable insights that drive growth and innovation.

We provide use-case driven generative AI solutions for faster, reliable results.

We develop new-generation AI solutions that analyse your company's documents and create new, valuable content. We use advanced techniques like GANs, VAEs, and Diffusion Models to generate unique content. We also build custom small and large language models using Transformers or modify existing models to fit your specific needs. To improve efficiency and accuracy, we use pre-trained models and fine-tune them for your specific tasks. We can help you integrate popular AI models like GPT4, BERT, MUM, PaLM, and others into your existing applications.

Development of LLM powered tools that are trained on custom data that can be fed, and interact with users around this data based on their prompts. We help organizations perform document analysis and extract information, utilizing NLP techniques to extract valuable insights from unstructured documents, enhance search capabilities, and perform end-to-end document analysis, enabling organizations to make informed decisions based on the extracted information.

Multi-agent bots to create conversations with multiple personas for users to interact with various intents simultaneously. Product Innovation with focused groups and task forces, 24x7 customer support, emergent actions with case management, Marketing, Training and Education, etc. with Agentic AI solutions. Q & A Assistant that saves time with conversational search.

Automated generation of content based on user prompts with the ability to modify formats and summarize key information. Various use cases are product information, blogs (1500+ words blog posts in two hours), case studies (Provide Insights, Proof Points to drive trust and growth), social media copies (Unlimited content, multiple tones), investor relations (from 10K filings), press releases (Save time, reduce errors), etc.

Development of analytics engine and to automate the analysis of large data sets and automate the development of dashboards to provide operational insights in a consumable manner.

Make your business more efficient with aurotek ChatGPT integration services. Harness the power of OpenAI’s ChatGPT API to create intelligent, dynamic, and human-like applications that redefine the way businesses interact and operate.

Enablement Framework

Experience a seamless journey to AI transformation with our proven enablement framework

Generative AI is poised to be a $1.3 trillion market by 2032, with an expected CAGR of 42% over the next 10 years. Gen AI represents a disruptive technology that can help unlock a piece of the unrealized improvement potential. Disparate sources of unstructured data are now assets to power Gen AI applications. However, Gen AI also raises significant challenges, including accountability, patient trust, bias, and data security. Unlock the full potential of your Gen AI initiatives with our proven and adaptable framework; Gen AI Enablement Framework, GenAI co-creation POD engagement model with top-tier talent, and future proofing considerations

Gen AI Enablement Framework

Our enablement framework is based on ‘Ideate, Innovate, Transform’ iterative cycle.

Ideate: Discovery of Use Cases

Ideal use case is at the intersection of Desirability - one that your customers and employees really want and solving the right pain point, Feasibility - builds on the strengths of current operational capabilities and matches the future business requirements, and Viability – deliver sustainable business value.

Assess the feasibility of the use case on the dimensions of
  • Level (Prompt, RAG, Agent)
  • Deployment (Batch, On-demand),
  • Automation (Human in the loop, Fully Automated)
  • User (Internal or External)
  • Task (Specific or Open-ended)
  • Model (Vendor API, Open Source, Tuned)
  • Data (Public, Enterprise, Synthetic, Sensitive)
Artificial Intelligence Development Services

GenAI co-creation POD engagement model

Future Proof the solution with these considerations

Tool Agnostic Development

AI tools must be developed by leveraging multiple LLMs to create a flexible tool agnostic environment and reduce the lock in dependencies of a single tool

Adaptive Knowledge Acquisition

To deliver the latest content to users, the data integration loop from the sources must be automated

Data Privacy and Security

It is critical to develop a self-contained infrastructure for the tool which will avoid data exposure to LLM’s and will maintain data privacy and security

Guardrails for AI Hallucinations

Creating guardrails to prevent AI hallucinations and misinformation is key to improving the quality of the experience of LLM based tools

Development Process

AI powered Innovation mandates a disciplined development process to ensure compliance and business impact

Our seasoned Generative AI developers take a holistic approach to understanding your objectives and goals. As a dedicated Generative AI development services company, we endeavour to develop a fit-for-purpose, scalable, immersive, and seamless Generative AI solution tailored to your audience persona.

As a pioneer in generative AI services, we begin the development process with use case refinement. Understanding mission critical priorities and KPIs that can be improved by AI use cases helps in detailing of the use cases in terms of data needs, models selection, fine-tuning and task specialization, finer integration nuances, specific security and compliance requirements. Well defined use cases serve as clear terms of reference for measuring impact, before diving deep into the development.

As a responsible generative AI services company, we know the importance of data in building an effective solution. This phase involves comprehending the client’s goals and needs by collecting information on the intended functionality, target audience, and business objectives. This ensures that the generative AI solution aligns with the client’s vision. Subsequently our expert team organizes the essential data to train the generative AI models. This comprises obtaining the datasets, refining and prepping them, and validating their quality and reliability to ensure precise model training.

Building Customized AI Solutions involves leveraging of advanced deep learning algorithms, foundational models keeping the objectives, scope, and context in mind. The models learn from the provided training dataset, discerning patterns and generating outputs. Through iterative fine-tuning, the training process optimizes the model’s performance, ensuring it generates the desired output with enhanced accuracy, reliability, and effectiveness, minimizing bias, hallucinations, and risks.

After the generative AI models are trained, they undergo a thorough verification and validation process. This includes evaluating the model’s performance, accuracy, reliability, explainability, , responsibility, integration, quality and robustness. Our rigorous testing process and testing techniques carried out during the development to rectify issues before deploying the solution.

After the generative AI solution has been successfully verified and validated, it is deployed and integrated into the client’s existing systems or applications supporting the business processes or tasks. The integration process is carefully executed to ensure seamless integration with the interfaces, round-trip performance, cost optimization, compatibility, and scalability to support the client’s operational needs.

Continuous monitoring and optimization are essential for the user adoption and consistent performance of the generative AI solution after deployment. This stage of generative AI software development includes ongoing enhancements, scaling, and process optimization, monitoring for issues, updating models, adaptive knowledge acquisition, and incorporating user feedback to improve the solution over time.

Technology Stack

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We’re happy to answer any questions you may have and help you determine which of our services best fit your needs.

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