One platform for knowledge, operations, and governance.
Hypercloud delivers a private knowledge fabric, a pattern‑learning engine for operational data, and a compliance‑first governance layer—built to run inside your perimeter.
Private Enterprise Knowledge Fabric
In‑perimeter knowledge fabric across docs, tickets, wikis, code, and logs—with RAG, citations, and secure LoRA personas.
Pattern‑Learning Engine
Learns operational event patterns to predict incidents, outcomes, and failure modes—fully private.
AI Governance & Compliance
Central control plane for private LLMs with policy enforcement, lineage, audits, and risk monitoring.
Platform
A private AI foundation that runs inside your perimeter—designed for knowledge, operational intelligence, and governance.
Private-by-Default
Runs in your VPC or data center with customer‑managed keys and strict data residency controls.
Unified Retrieval
Connects documents, tickets, code, and logs with RAG, citations, and permission‑aware access.
Governed AI
Policy enforcement, audit logs, and model lineage to meet enterprise compliance requirements.
Private Enterprise Knowledge Fabric
Secure, in‑perimeter platform that turns corporate information into an AI‑accessible knowledge fabric—without using public LLM APIs.
- Deploy in customer VPC or data center (K8s/VM), using customer GPUs or isolated managed clusters.
- All data stays in customer object storage + vector DBs with customer‑managed keys and VPC controls.
- Connectors for M365/Google Workspace, Confluence, Jira/ServiceNow, GitHub/GitLab, data warehouses, logs.
- RAG with metadata‑aware retrieval and inline citations back to source documents.
- Department personas via LoRA adapters tuned on support, engineering, or legal data.
- Security-first: IAM/RBAC, zero retention, full audit logs of prompts and sources.
- Productivity lift: 10–30% less time searching; faster onboarding.
- Annual subscription by users/connectors; optional LoRA packs and managed retrieval quality.
Pattern‑Learning Engine for Operational Data
Learns the language of operational events (logs, telemetry, IoT, customer journeys) to surface early warnings and outcomes—privately.
- Transform event streams into compact synthetic tokens encoding state and metrics.
- Periodic LoRA training in customer cloud/GPU environment to predict next states and failure modes.
- Pattern discovery: early‑warning sequences and root‑cause hints.
- Scenario querying with likely outcomes and rough probabilities.
- Generalizable across IT ops, manufacturing, logistics, customer funnels, fraud.
- Reduced downtime and churn via early detection and better runbook selection.
- All data stays in customer infra; only LoRA adapters persist for inference.
- Base platform fee + usage‑based training windows; optional consulting for event languages.
AI Governance, Ethics & Compliance Orchestrator
Centralized control plane for governed private LLMs—covering security, ethics, compliance, and lifecycle management.
- Blueprinted architectures for AWS/GCP/Azure/on‑prem with private endpoints and residency controls.
- Model registry for base models, LoRA adapters, and RAG pipelines with full lineage.
- Policy authoring with enforcement and human‑in‑the‑loop gates.
- Bias and harm monitoring with evaluation suites and remediation workflows.
- Audit logs and structured evidence packs for regulators and model‑risk committees.
- Prevents shadow AI by offering sanctioned, well‑governed paths.
- Standardizes RAG + fine‑tuning across teams and integrates with GRC and identity systems.