Hyper vs SapienX: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Hyper and SapienX — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Hyper
Hyper
A company knowledge layer that learns from Docs, Slack, Email and Calendar to power smarter, context-aware AI across teams.
Key features
- Unified Knowledge Ingestion: Continuously imports and indexes data from Docs, Slack, Email, and Calendar to build a central, searchable company knowledge graph.
- Contextual AI Plug-ins: Provides an interface and connectors so teams can inject company-specific context into external or internal AI models, improving accuracy and relevance of responses.
- Persistent Institutional Memory: Retains historical context across conversations and workflows so the system remembers past decisions, preferences, and policies without manual re-entry.
- Real-time Sync and Updates: Keeps ingested sources up to date with near real-time synchronization so answers reflect the latest documents, messages, and schedule changes.
- Access Controls & Security: Enables role-based access and privacy controls to ensure sensitive documents and communications are only used where permitted.
- Searchable Knowledge Retrieval: Offers semantic search and retrieval of relevant docs, messages, and calendar events to surface precise context for queries and automations.
- Workflow Automation: Leverages stored knowledge to trigger or assist with routine tasks (e.g., follow-ups, meeting summaries) and reduce manual work.
- Integration Framework: Supports connectors and APIs to integrate with common productivity tools and plug the company brain into existing AI assistants or platforms.
- Ingests and learns from Docs, Slack, Email and Calendar
- Creates a centralized, searchable company knowledge layer
- Integrates/"plugs into" existing AI systems to provide context and memory
- Context enrichment for downstream AI responses and workflows
- Connectors to common collaboration sources (Docs, Slack, Email, Calendar)
Best for
- Onboarding Acceleration: New hires query the company brain to get accurate, contextual answers about processes, past decisions, and team norms without repeatedly asking colleagues.
- Customer Support Enablement: Support agents retrieve up-to-date product docs, past tickets, and policy notes to craft faster, consistent responses to customers.
- Meeting Summaries & Action Items: Automatically summarize calendar events and linked documents, then surface follow-ups and owners based on historical context.
- Internal Knowledge Discovery: Employees search across Slack, emails, and docs to find precedents, design decisions, or technical notes relevant to current projects.
- Automated Follow-ups: Use contextual knowledge to draft or schedule follow-up emails and tasks after meetings, ensuring continuity and reducing manual tracking.
- Compliance & Audit Readiness: Aggregate and index communications and documents to simplify internal audits and demonstrate policy adherence with searchable records.
- Developer and Product Support: Engineers and PMs query past architecture decisions, bug histories, and release notes to speed troubleshooting and planning.
- Provide company-specific context to LLMs and AI assistants
- Centralized knowledge retrieval and enterprise search across Docs, Slack, Email and Calendar
- Faster onboarding by surfacing institutional knowledge
- Automated summarization and context-aware drafting for email and meetings
- Enriching customer-support or internal automation agents with up-to-date company info
SapienX
SapienX
AgentOS: a human operating layer for OpenClaw to create, manage, observe, and run local-first AI agents with context, policies, and approvals.
Key features
- Workspace and Mission Mapping: Organizes work into persistent missions that correspond to real project folders, enabling reproducible agent runs and linking outputs (files, transcripts) to projects for later inspection.
- Runtime Inspection and Replay: Captures and exposes runtime output, created files, and transcript history so humans can inspect agent decisions, debug behavior, and audit outcomes after execution.
- Presets, Policies, and Memory: Provides structured agent team configuration including reusable presets, policy enforcement, memory management, and workspace scaffolds for repeatable operating conventions.
- Health, Metrics, and Observability: Centralized dashboard to view agents, models, runtimes, and system health with diagnostics to monitor multi-agent workflows and track performance/costs.
- Local-first CLI and Launcher: Distributed as a local-first application with a packaged launcher and CLI commands (e.g., agentos start, agentos doctor) for easy local installation, startup, and runtime verification.
- OpenClaw Integration: Built on the OpenClaw orchestration kernel to coordinate agents and runtimes while providing a human control layer on top for approvals and manual interventions.
- Control-plane UI for creating, managing, and observing AI agents and workspaces