Platform, IT and security manage workspaces, model access, budgets and audit in one place.
Enterprise AI agent platform
Bring AI agents to your whole company, without losing control.
Your people already use tools like Claude, Codex and Trae on their own. Stacklane-ai runs them in one managed place, so cost, security and know-how stay with the company instead of scattered across personal accounts.
At a glance
Stacklane-ai sits between your people and the AI tools.
Your teams
Engineering
Marketing
Operations
Finance
Stacklane-ai
One managed layer
AI tools & models
Claude Code
Codex
Trae
DeepSeek
Fable
Everyone reaches AI through one place you control, so cost, security and know-how stay with the company.
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.
Why teams need this
When everyone uses AI tools on their own, four problems show up.
We ran AI agents across our own company first, with people using them every day. These are the pain points that appeared, and the reason we built Stacklane-ai.
Cost you can't see
Spend spreads across personal subscriptions and API keys, with no single number for the company.
Know-how walks out the door
Good prompts, results and history live in private chats and leave when people do.
No record for security
When something goes wrong, no one can show what an agent read, changed or sent.
Everyone rebuilds the same thing
Each team writes the same prompts and workflows from scratch, again and again.
Tools vs. platform
Handing out AI tools is not the same as running AI in your company.
The tools write the work. Stacklane-ai is how a company runs, sees and keeps that work.
Just handing out AI tools
- CostScattered across personal accounts, invisible to finance.
- KnowledgeTrapped in private chats, lost when people leave.
- SecurityNo record of what agents read, changed or sent.
- ConsistencyEvery person works a different way.
- New teamsStart from zero every single time.
Running AI on Stacklane-ai
- CostOne view of spend by team, project and model.
- KnowledgeReusable company skills and templates that stay.
- SecurityEvery session tied to a person and a project.
- ConsistencyOne approved way for everyone to start.
- New teamsLaunch from a ready template in minutes.
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-ai 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.
Buyer conversations
The questions enterprise teams ask before they standardize AI agents.
The questions we hear most often about fit, value and rollout.
Buyer
What exactly is Stacklane-ai?
Stacklane-ai
Stacklane-ai is an enterprise AI agent workspace governance platform. It gives platform teams one console to manage workspaces, model access, templates, budgets and audit evidence while employees run agents inside approved project spaces.
Buyer
What problem does it solve for a company already using AI tools?
Stacklane-ai
It turns scattered AI usage into managed operations. Instead of personal accounts, unmanaged API keys and invisible project history, teams get controlled workspaces, shared context, usage records, budget visibility and reusable practices.
Buyer
How is this different from ChatGPT, Claude or DeepSeek?
Stacklane-ai
Those are models or AI tools. Stacklane-ai is the operating and governance layer around the work: projects, members, model channels, equipped skills, quotas, files, logs and approval evidence.
Buyer
Can security and finance see what agents are doing?
Stacklane-ai
Yes. Stacklane-ai keeps AI work tied to people, projects, model routes, files, tool activity, cost and audit history so risk, spend and evidence do not disappear into personal chats.
Buyer
Can good prompts and workflows become company assets?
Stacklane-ai
Yes. Review checklists, prompts, delivery templates and operating procedures can be published as reusable skills, then equipped by teams per project instead of being rebuilt from scratch.
Buyer
What does a pilot usually evaluate?
Stacklane-ai
A pilot usually maps your team structure, identity system, repositories, model providers, budget rules and compliance needs into a small set of governed AI workspaces.
Pilot
Plan a governed AI workspace pilot.
We can map Stacklane-ai to your team structure, model providers, repositories, access system and compliance needs.
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