Connect operational knowledge
Bring telemetry, topology, incident history, runbooks and vendor documentation into the reasoning process.
nLLM
nLLM™ is Invences’ network-specific intelligence layer, designed to connect telemetry, topology, runbooks and incident history to investigation and recommendations. It supports iFabric’s agentic workflows and can connect to configured ITSM processes.
Explore nLLM See architecturenLLM / How it works
Prepared knowledge. Current evidence. Grounded reasoning.
Retrieve context. Reason. Hand off guidance.
Recommendations enter configured iFabric or ITSM workflows. Consequential actions require the deployment’s authorization and customer or partner execution tools.
Prepare operational knowledge as a searchable index. At runtime, combine relevant retrieved material with a question and current infrastructure evidence to investigate likely causes and recommend next steps. Knowledge preparation and runtime inference are separate processes.
Prepare operational knowledge as a searchable index. At runtime, combine relevant retrieved material with a question and current infrastructure evidence to investigate likely causes and recommend next steps. Knowledge preparation and runtime inference are separate processes.
This is an illustrative architecture, not a live product demonstration or customer result. The knowledge-preparation band and runtime band are separate: current telemetry supplies request context, not instant model retraining. The prepared-index connection represents retrieval access rather than a fresh preparation cycle for every question. Define corpus ownership, model configuration, evidence sources, access rules and workflow integrations for the environment. No particular model version, corpus size or reasoning accuracy is implied. Review for insufficient context is an illustrative proposed exception flow to confirm in deployment scope. Animation timing is illustrative; repetition restarts the explanation, not an operational action.
Live reasoning. A question and current infrastructure evidence enter runtime retrieval. Relevant prepared knowledge grounds the reasoning and resulting recommendation. Guidance reaches a configured workflow, where any consequential action still requires authorization. This path does not retrain the model or update the knowledge corpus.
Knowledge preparation. Selected runbooks, documentation and incident history are prepared as a scoped corpus and searchable index through the configured knowledge pipeline. This process is separate from a live request and ends before runtime inference; it does not depict a model-training cycle.
Insufficient context. The available runtime evidence and retrieved context are insufficient to support a next step. This illustrative review path ends with an operator gathering or checking context. It does not continue to workflow handoff or execution. Confirm this exception handling in the deployment scope; it is not a claim of confirmed native behavior.
nLLM / In focus
nLLM supplies reasoning for iFabric’s autonomy capabilities and can connect to an enterprise’s existing ITSM workflows. Its guidance draws on the systems, evidence and procedures relevant to the environment.
Capabilities
Bring telemetry, topology, incident history, runbooks and vendor documentation into the reasoning process.
Use infrastructure context to investigate incidents, explain likely causes and propose next steps.
Connect reasoning to iFabric and ITSM workflows, with actions subject to the deployment’s policy and authorization.