Requivo vs General LLM Models
LLMs generate outputs. Requivo builds a governed operational knowledge layer that stays inside the organisation.
The table below summarises the practical difference between Requivo and general-purpose LLM models such as ChatGPT, Claude, and similar assistants.
| Dimension | Requivo | General-purpose LLMs e.g. ChatGPT, Claude |
|---|---|---|
| What it is | An operational knowledge system | A general-purpose AI assistant |
| What it creates | A governed operational knowledge layer that stays in the organisation | Responses, drafts, summaries, and analysis |
| What it works with | Large volumes of scattered enterprise information, documents, workflows, and expert know-how | Prompts and context supplied by the user |
| Role of experts | Expert elicitation and validation are built into the core workflow | Expert input depends on the user’s own interaction with the model |
| How knowledge is handled | Builds a maintained knowledge layer with structure, validation, and ownership | Uses available context to produce an immediate answer or output |
| How gaps are handled | Continuously surfaces weak, missing, or conflicting knowledge areas and routes them into structured expert follow-up | Can identify gaps or conflicts when prompted, but only within the current interaction |
| Long-term value | Builds a reusable organisational knowledge asset | Produces useful outputs, but not a maintained knowledge layer by itself |
| Enterprise fit | Model-flexible by design, allowing organisations to align model choice, infrastructure, and data-residency requirements | Usually tied to the model, policies, and infrastructure of a specific provider |
LLMs respond to the context available in the moment. Requivo turns fragmented enterprise information into a governed operational knowledge layer.
LLMs can identify gaps or conflicts when prompted. Requivo surfaces them systematically and routes them into expert follow-up.
LLMs produce useful outputs. Requivo builds a reusable organisational knowledge asset that can be maintained over time.
Requivo turns fragmented enterprise information and expert know-how into a governed operational knowledge layer — a reusable organisational asset that can be validated, maintained, and used across teams, workflows, and AI systems.
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