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Azure OpenAI Full Fledged Product - Deployment & Scaling: 2-6 weeks
Implementing feasible, secure, cost-effective & highly customized Generative AI use cases
After thoughtful consideration, you've identified a specific GenAI use case for implementation using Azure OpenAI - a strategic move demanding a holistic approach for successful execution. You stand at the crossroads, poised to make informed decisions, yet wary of falling into the 'proof-of-concept' pitfall, where initial success faces resistance when it comes to scaling. The promise of AI encounters roadblocks in infrastructure and user adoption. Now you are seeking best practices and experts to help you implement technologically feasible and economically viable GenAI use cases? Considering which model suits your use case best? Whether it's Product and Industrial Design, Data Augmentation, Personalization and Recommendation Systems, Chatbots, Virtual Assistants, or medical research, our extensive experience in numerous implementations ensures efficient and secure executions. We specialize in decoding the puzzles, unlocking scalability, and offering actionable advice. We've lived through it, conquered it, and we're here to support you through every twist and turn.
Our implementation starts by leveraging predefined solutions from our Accelerator service, encompassing a range of infrastructure and code solutions finely tuned for Azure OpenAI use cases. We execute rapid deployment through Infrastructure as Code (IaC) and then proceed to customize, optimize, and build a full-scale solution tailored to your specific needs. Reflecting on our past experiences, it's clear that focusing on specific risks is paramount. We prioritize addressing unique GenAI risks—like privacy breaches, hallucinations, biases, and copyright concerns. In the same time we believe in optimizing technology choices by meticulously balancing costs and rewards. This includes choosing between developing a new language model or leveraging existing ones, deciding on layers, service integrators, cloud-based or on-premises systems, open source or proprietary models, and addressing confidentiality aspects. Our strong recommendation is to approach all these considerations while adhering to pivotal principles: accuracy, empowerment of human decision-making, sustainability, ethics and safety. Our extensive pool of talent encompasses Cloud Architects, Data Engineers, Data Scientists and Full Stack Engineers with expertise that extends beyond conventional deployment parameters. Their expertise lies in the Azure infrastructure, encompassing key services:
Target Audience & Value
Our collaborative approach typically involves engagement with Project Managers and Technical Experts. Unit8 will ensure a seamless and successful implementation of Generative AI, leveraging Microsoft Azure cloud ecosystem. During Azure OpenAI deployment, we facilitate a comprehensive process—from documentation, prompting, developing user-friendly interfaces, to the logic, applications, and operational specifics tailored to GenAI. We set up the right framework, language models, methodologies. Our knowledge-sharing ethos involves close collaboration with your internal teams, ensuring knowledge transfer throughout the project lifecycle. We leverage our experience from various real-world projects & we implement data extraction models for diverse needs—from candidate resumes to insurance contracts and financial documents. Among our showcased projects is the successful deployment & adoption of four secure, internal GPT chat platforms.
Takeaways/ deliverables/ Outcome:
Depending on the complexity the estimated time is from 2 to 6 weeks per Use Case.