EnterpriseWeb is Automating the Entire Software Development Lifecycle with Generative AI

The company premiers two new IT use cases: Complex Integration and Code Support

Jun 26, 2024

Link to YouTube demo: https://www.youtube.com/watch?v=fbn8APhkwCU

EnterpriseWeb is an AI-enabled no-code platform for intelligent automation. It empowers developers to design, deploy and manage context-aware business and infrastructure applications. The platform is built around a graph knowledge base, which serves as a Domain Specific Language for the declarative design environment. The graph DSL simplifies and automates routine IT tasks to improve developer experience and productivity. The platform’s run-time leverages the graph for real-time interaction context to interpret the events, automate decisions and optimize actions. EnterpriseWeb supports multi-model generative AI with ModelOps and hybrid AI for AIOps. 

The Platform technology is based on agents, hypergraphs and serverless functions – a horizontal architecture for complex event processing. EnterpriseWeb supports complex, real-time, multi-step contextual automation and long-running processes, with strong IT governance.

The platform streamlines the integration, use and management of LLMs. No static, one-off RAG pipelines per use case for each LLM/version. No writing custom Python code per use case for each LLM/version. No static, one-off manual integrations per use case for each LLM/version. EnterpriseWeb simplifies and automates LLM interactions with a platform-based workflow.

Last fall, the company won an industry award for its ground-breaking work on “enterprise-grade generative AI for service orchestration” in collaboration with Microsoft.

EnterpriseWeb provides a practical approach to generative AI that leverages its strengths while mitigating its weaknesses – 

1. Reduce LLM costs and accelerate time-to-value by minimizing training, tuning, prompts, and tokens

2. Mitigate security, legal and sustainability concerns by shifting processing away from the LLM to secure and efficient back-end automation systems

3. Contextualize LLM outputs by grounding them with domain knowledge so they can be understood deterministically

4. Translate intent into action by enabling developers to “talk to the EnterpriseWeb” to design, deploy and manage complex services transforming the end-to-end SDLC 

5. Enable AI at the edge – EnterpriseWeb’s edge-optimized footprint (50MB) enables it provide full GenAI and AI automation solution for secure, local low-latency processing with the customer workloads

In this presentation, the company demonstrates two general business use cases: 

1) GenAI for ETL, where the developer can talk to the platform to compose a complex, enterprise-grade data integration, with the platform generating and implementing the interfaces and the ETL workflow; and 

2) GenAI based code support – optimizing code summarization, analysis and recommendations. Outputs with EnterpriseWeb leveraging our graph are far more correct, clear and concise than any Copilot type solution. 

Enjoy the presentation!

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