Built on OpenClaw and designed for containerized deployment. Manage multiple agents, knowledge bases, messaging integrations, monitoring, and usage costs from one clean control panel.
From agent creation to monitoring and operations, the platform covers the full lifecycle of enterprise AI agents.
See all agent states at a glance, with real-time CPU and memory trends to keep operations clear and visible.
Each agent runs in its own container, with one-click create, start, stop, restart, and bulk actions across agents.
Connect OpenAI, Anthropic, DeepSeek, and compatible self-hosted APIs, all behind one routing layer.
Install new capabilities from a skill library or upload custom skill packages to extend each agent.
Keep complete chat records for every agent and review user interactions in a structured timeline.
Define persona, role, naming, and system prompts so each assistant fits its business purpose.
Support Feishu, WeCom, DingTalk, Slack, official WeChat accounts, and other team communication channels.
Track token usage and estimated costs by agent and by user, with clear trends over time.
JWT auth, encrypted API key storage, and audit logging help teams operate safely and with traceability.
Each agent can keep its own knowledge base, with drag-and-drop uploads and previews for text, images, and PDFs.
Clone agent settings, knowledge files, and skill bindings to launch a matching agent in seconds.
Set model pricing once and let the platform automatically estimate spend from actual usage.
Monitor storage usage across agents, backups, and skills, with warnings before space becomes a problem.
Export chat logs and audit records as CSV for reporting, archiving, or further analysis.
These are the questions teams usually ask before moving forward, so you can quickly judge whether the platform fits your use case.
It is not just one chatbot. It is a control layer for running many AI agents across multiple teams, roles, and workflows from one platform.
Most AI assistants serve one narrow use case. HaiHe Agent is designed for enterprise operations, with centralized control, observability, integrations, and long-term maintainability.
Yes. The platform can run on your own cloud servers or internal infrastructure, and it can connect to your existing model gateway if needed.
Yes. It fits Feishu bots, WeCom assistants, DingTalk workflows, and can be extended to Slack, official WeChat accounts, and API-based integrations.
You can track usage by agent, user, and team, while assigning separate knowledge bases, model routes, and access rules for different business units.
It works well for support teams, sales enablement, internal knowledge assistants, content teams, legal and finance workflows, and engineering operations.
Deployments, knowledge bases, messaging channels, live status, and cost tracking all live in one place.
Manage all business agents from one server and one routing layer, while keeping each agent isolated in its own runtime.
Dedicated knowledge bases make each agent more accurate and much more useful in its own field.
Session-based history keeps context intact and makes reviews far easier for operations teams.
Visual dashboards show overall health, while failures trigger alerts automatically so teams can react earlier.
Each agent runs in its own isolated container, keeping the system clean, resilient, and scalable.
These are the kinds of workflows where teams usually see clear value quickly.
A company running five online stores can deploy one support agent per store, each with its own product manuals and policies. Customers ask questions in Feishu, agents reply instantly, and management sees usage and cost by store.
A mid-sized law firm can run separate agents for labor law, contract review, and IP. Each agent keeps its own regulations and case files, while all conversations remain auditable for compliance.
An agency managing multiple brands can assign one content agent per brand, each trained on its tone and best-performing references. Teams can use different agents for social posts, long-form assets, or SEO work.
A 20-person engineering team can deploy separate agents for code review, API docs, and infrastructure support. New hires ask the agents instead of interrupting senior teammates, and answers stay grounded in internal docs.
A real estate chain can give each branch its own agent with branch-specific listings and scripts. Customers get fast first responses, while headquarters tracks performance and costs by location.
JWT-based auth protects the admin surface and secures API access across the platform.
API keys are stored with encryption, reducing exposure risk even if the database is compromised.
Critical actions are recorded automatically and can be filtered or exported for reviews.
Combine scheduled and manual backups, with database dumps and config archives ready for recovery.
When agent status changes unexpectedly, alerts can be pushed to Feishu with cooldown controls.
Each agent runs in its own Docker container, so faults and resource pressure stay isolated.
Suitable for pilot projects, small teams, and formal production use. Model API and infrastructure costs are billed separately.
See a live demo first, then decide what deployment and integration path fits your team best.