Case study: Technology & SaaS
Bringing real-time intelligence into enterprise assistants
A large enterprise technology organization whose employees were spending significant time each day manually searching across multiple systems to find information needed for basic decisions and daily work.
The challenge
Fragmented systems were creating an invisible but costly productivity drain across the organization:
- Knowledge distributed across enterprise systems, repositories, and external sources with no unified access
- Employees averaging significant time per day on information retrieval before productive work could begin
- Existing search tools returning unfiltered results requiring extensive manual review and judgment
- No ability to synthesize information from multiple sources into contextually relevant responses
- Low-value interruptions and notifications consuming time that should be spent on high-impact work
The business impact
- Information retrieval time reduced substantially as employees access knowledge through a single interface
- Decision quality improved as real-time and synthesized information became available at point of need
- Employee productivity increased as time previously spent searching was redirected to productive work
- Cross-system information synthesis achieved at scale, eliminating the need for manual cross-referencing
- Digital workplace experience transformed through an intelligent assistant covering daily information needs
The solution
JBS developed a multi-LLM enterprise AI assistant enabling:
- Multi-LLM orchestration framework selecting the most appropriate model for each query type and complexity
- Live web and enterprise knowledge retrieval connecting the assistant to internal and current external data
- Persistent contextual memory maintaining relevance and coherence across extended interactions
- Conversational analytics capability allowing employees to query and interrogate data through natural language
- Role-based knowledge access ensuring information security and compliance within the unified assistant
Technology & SaaS AI capability at enterprise scale
JBS approaches this use case as a production-grade operating capability, aligning AI engineering, workflow design, governance, and measurable business outcomes.
How the solution works
The solution combines domain context, automation, quality review, and integration into operational workflows so teams can move faster without losing control.
Results achieved
Information retrieval time reduced significantly through the unified AI assistant experience
Employee productivity measurably improved as knowledge access friction was eliminated
AI assistant adoption strong across the organization due to quality, breadth, and reliability of capability
Why JBS
- Advanced expertise in multi-LLM orchestration and enterprise AI architecture design
- Experience integrating AI with complex enterprise knowledge systems and data sources at scale
- Strong capability in designing persistent memory and context management for enterprise assistants
- Security and compliance focus ensuring enterprise AI deployments meet all governance requirements
Frequently asked questions
How does this AI solution work?
It maps the business workflow, identifies repeatable decision points, and applies AI where it improves speed, quality, consistency, or scale.