Organizations can have many different possible use cases for GenAI, but they may not know which ones should be pursued. We assist in prioritizing applications by Business Impact, Feasibility, Data Readiness, and Implementations Complexity.

Foundation models provide great responses, but they might not be aware of your internal policies, products, processes or proprietary knowledge. Utilize RAG and prompt engineering and model adaptation to align AI outputs to relevant business context.

Many important data points are spread across documents, databases, CRMs, ERPs, knowledge bases, SharePoint sites and other enterprise systems. GenAI applications require safe access to the proper information, while maintaining security and governance.

Enterprise AI introduces new considerations around sensitive data, access control, model usage, data residency, auditability and AI governance. We incorporate security and governance considerations into the architecture rather than treating them as an afterthought.

The ever-evolving GenAI landscape includes a variety of foundation models, APIs, orchestration solutions, and deployment strategies. We build flexible architectures that enable organizations to change their AI stack without having to reprovision applications every time.

Identify the areas in which generative AI can bring value to the business before investing substantial resources in the development. Our experts can assist with the evaluation of AI opportunities, technology and data readiness assessment, prioritization of use cases and implementation roadmap.

Build unique GenAI applications that fit your workflow, users and business needs. We create tailored applications that integrate enterprise interfaces, business logic, APIs, databases and existing systems with generative AI features.

Integrate large language models into your applications without rebuilding your technology ecosystem from scratch. We help select and integrate suitable foundation models based on factors such as capability, latency, cost, context requirements, deployment model and data sensitivity.

Make generative AI more useful for enterprise knowledge by connecting models to trusted business information. Sphinx designs RAG architectures that retrieve relevant information from approved data sources and provide it as context to the AI application before generating a response.

Build conversational experiences that go beyond scripted chatbot interactions. Our GenAI chatbot solutions can combine LLMs, enterprise knowledge, conversation history, APIs and business workflows to deliver context-aware interactions across websites, applications and internal platforms.

Leverage GenAI to enhance the efficiency of software development processes, from writing and understanding to testing and maintenance. We create AI-powered engineering solutions that integrate with the current development processes, repositories and environment.

Give employees faster access to relevant data via AI powered enterprise search, knowledge assistants and conversational interfaces.

Use conversational AI and personalized content generation to provide faster, more context-aware customer interactions.

Automate document processing, reporting, content creation, support and other knowledge-intensive processes.

Support development teams in creating code, writing tests, and gaining insight into legacy applications to help speed engineering processes.

Use GenAI to integrate with business information such as reports, documents, databases and operational information for natural-language interaction.

Generate and transform business content while maintaining appropriate brand, terminology and governance controls.

We start with your business challenge, not with a particular AI model. We determine the use cases and assess their feasibility and establish an implementation roadmap that fits with tangible business results.

We build GenAI applications with the architecture required for real-world enterprise environments including scalability, reliability, observability, integration and maintainability.

We assess foundation models to suit your needs in terms of accuracy, performance, context processing, privacy, deployment flexibility and cost, and help you select the technology that meets the use case.

Security and governance is considered throughout the development lifecycle. Access controls, data protection, auditability, human oversight, and AI evaluation and responsible AI practices can be integrated into GenAI solutions.

GenAI becomes more valuable when it can work with the systems employees already use. We integrate AI with enterprise applications, databases, APIs, SharePoint, Microsoft 365, CRM, ERP and business workflows where required.

Our multidisciplinary capabilities across AI, application engineering, cloud, data, DevOps and cybersecurity help address the technical challenges that arise when taking GenAI into production.