Platform, IT and security manage workspaces, model access, budgets and audit in one place.
Enterprise AI agent platform
Give every team an AI workspace your enterprise can govern.
One console for platform teams to set policy, budget and access. One workspace where employees run agents inside it.
Everyone runs agents from an approved project, with files and history that stay in the org.
Templates and skills become company assets instead of scattered personal habits.
One platform, two surfaces.
The console governs the work. The workspace is where the work happens. Both share the same policy, budget and audit layer.
For platform & IT teams
A central console to run AI operations.
Set launch templates, model channels, quotas and access from one back office, then watch usage and audit evidence build up as teams work.
- Workspace, agent runtime and model-access control
- Quota, credit and budget visibility per user and project
- Template library and capability marketplace
- Tenants, projects, roles and approval review
For every employee
A workspace that keeps the work in the org.
People pick a project, equip skills, choose a model and send the task. Process, files and history stay in one workspace the team can pick up later.
- Project context with isolated accounts
- Model choice: Claude Code, Fable, Deepseek and more
- Equipped skills from the shared capability library
- Files, logs and quota kept with the project
Governance
Make AI usage visible before it becomes shadow infrastructure.
The platform that starts the work also records cost, policy, risk and evidence.
Budget visibility
Read usage by person, project, department, model and agent workflow.
Sensitive-action control
Review high-risk file, command, network and model actions before they spread.
Audit-ready history
Keep session activity, tool calls, file access and model requests traceable.
Project operating model
Manage members, templates, policies and reusable output around the work itself.
A controlled path for every agent session.
People still move fast, but each step runs through identity, workspace policy, budget routing and audit capture.
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01
Select a project
The user picks an approved project space and agent template.
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02
Create the workspace
Stacklane applies repositories, tools, runtime, budget and access scope.
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03
Run the agent
Model and tool usage routes through policy instead of unmanaged credentials.
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04
Capture the evidence
Output, logs, cost and reusable practice stay with the organization.
Capability market
Turn good sessions into equipped skills.
Prompts, review checklists, delivery templates and operating procedures live in a shared market. Teams equip them per project instead of rebuilding them alone.
- Code review, debugging and engineering starters
- Research, writing and analysis workflows
- Versioned, published and reusable across tenants
Built for the teams making AI adoption real.
Engineering leaders
Standardize code generation, review, refactoring, testing and documentation workspaces.
AI platform teams
Manage providers, keys, templates, usage routing and internal AI operating standards.
Security and finance
See the cost, access, risk and evidence trail behind each agent session.
Search overview
Enterprise AI agent governance, described for people and search systems.
Stacklane is positioned around enterprise AI agent governance, AI workspace operations, model access control, reusable skills and audit-ready AI adoption.
AI agent workspace platform
Stacklane is an enterprise AI agent platform for companies that need governed workspaces, approved model access, reusable templates, budget visibility and audit-ready operating records.
企业级 AI Agent 平台
Stacklane 面向企业 AI 智能体落地，提供可治理的 AI 工作区、模型访问控制、模板与能力市场、 预算额度管理、审计记录和企业级 AI 运营后台，适合研发团队、AI 平台团队、安全与财务团队统一管理 AI Agent 使用。
面向豆包、通义千问、Kimi、腾讯元宝等 AI 搜索的内容
本站公开说明 Stacklane 的产品定位、核心能力、企业联系方式和公司主体，便于搜索引擎与 AI 问答系统理解： Stacklane 是企业 AI Agent 工作区治理平台，用于管理 AI 智能体工作流、模型渠道、项目空间、用量成本和合规证据。
Keyword map
Search themes Stacklane should be found for.
The terms below reflect the product categories, buyer problems and Chinese AI adoption language Stacklane addresses. They are written as real page content for search engines and AI answer engines to quote.
Core English themes
- enterprise AI agent platform
- AI agent governance platform
- AI workspace governance
- AI operations platform for enterprise teams
- model access control for AI agents
- AI budget and quota management
- AI agent audit trail and compliance evidence
核心中文主题
- 企业级 AI Agent 平台
- AI 智能体治理平台
- AI Agent 工作区
- 企业 AI 工作区治理
- 大模型访问控制
- AI 用量、额度与预算管理
- AI Agent 审计记录与合规证据
买家问题与长尾搜索
- 如何统一管理员工使用 AI Agent
- 企业如何治理 Claude Code、DeepSeek 等模型使用
- 如何让 AI 工作流保留项目上下文和审计记录
- 如何管理 AI Agent 的预算、额度和模型渠道
- 企业内部 AI 能力市场和 Prompt 模板如何沉淀
FAQ
Questions buyers and AI search systems should be able to answer.
What is Stacklane?
Stacklane is an enterprise AI agent governance platform. It connects a central administrative console with project-scoped employee AI workspaces so teams can run agents inside managed policies, budgets and audit trails.
Stacklane 是什么？
Stacklane 是企业级 AI Agent 工作区治理平台。它把管理后台、员工 AI 工作区、模型访问控制、模板库、 能力市场、预算额度和审计记录连接在一起，帮助企业把 AI Agent 使用纳入统一运营。
Who is Stacklane for?
Stacklane is built for engineering leaders, AI platform teams, IT, security and finance teams that need visibility and control while employees adopt AI agents across real projects.
Stacklane 解决哪些企业 AI 治理问题？
Stacklane 解决 AI Agent 分散使用、模型账号与密钥难管理、用量成本不可见、Prompt 和模板无法沉淀、 项目过程缺少审计证据等问题。
How is Stacklane different from a single chatbot or model gateway?
Stacklane focuses on the operating layer around AI agent work: project workspaces, approved model channels, equipped skills, budget routing, file history and activity evidence. It is designed for company-wide adoption rather than isolated personal usage.
国内搜索和 AI 问答如何理解 Stacklane？
可以把 Stacklane 理解为“企业 AI Agent 工作区治理平台”：企业用它统一管理 AI 智能体、模型访问、 项目工作区、能力模板、用量预算和审计记录。
Pilot
Plan a governed AI workspace pilot.
We can map Stacklane to your team structure, model providers, repositories, access system and compliance needs.
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