Build AI. Keep control

With Stackbone, the people who know the process best build the automation using natural language. It becomes real code in your repository, so Engineering stays in control while Finance, Operations and Legal can see and understand what’s running.

Business view: an automation drawn as a graph next to the chat that built it.
Business builds, IT governs

Built by any team. Engineering stays in control

Any team can build and deploy an agent. Its work becomes real code that Engineering can audit, review, control, and operate, so every agent lives under the same technical standards as the rest of your software. Finance, Legal, Operations, and Sales get continuous visibility into the work and the reports they need.

01. Your team builds the agent.

Finance, operations, marketing, sales... Anyone in your company describes the process they want to automate. Stackbone builds the agent, connects the tools it needs, and runs it on sample data. It is real code from the first run, and it ships when the team asks for a release.

02. Engineering owns the code.

The workflow Stackbone built for your team is a TypeScript file in your repository, and every step on the canvas is a function in it. Engineering opens that file in its own editor to review, improve and optimize it, then ships it under the same standards as the rest of your software.

03. Every team sees the impact.

Business teams get their own view of how agents are performing. Finance can track cost savings, Operations can monitor performance, and Legal can keep an eye on compliance. Custom dashboards turn every agent’s activity into the metrics each team needs to measure its impact.

One platform

One platform, not a tool per person

Everyone works from the same agents, data and runtime, while each team gets the tools and visibility it needs.

Today

5 people, 13 logins. Each team keeps its own copy of the data and the logic, and the copies drift apart.

Operations lead
Operations
  • Zapier
  • Gmail
  • Slack
3 logins
Finance manager
Finance
  • Excel
  • Outlook
2 logins
Business analyst
Strategy & Analytics
  • ChatGPT
  • Google Sheets
  • Notion
3 logins
Software engineer
Engineering
  • GitHub
  • Claude
  • Linear
3 logins
Compliance reviewer
Legal & Compliance
  • Dropbox
  • DocuSign
2 logins

With Stackbone

Four views, one foundation. A change made in one layer is what every other layer sees.

Gmail Outlook Slack Microsoft Teams Google Drive Google Sheets Notion Salesforce HubSpot Zendesk Intercom DocuSign Asana WhatsApp
GitHub Linear Jira Supabase PostgreSQL Snowflake Airtable Stripe QuickBooks Xero Workday Shopify Dropbox
Security

Every agent runs inside the limits you set

Isolation, approvals and a full audit trail come with the runtime. Your security system is built before you even start.

Isolated by default

Each install runs in its own micro-VM, with its own scoped credentials and its own egress allow-list. An agent reaches the systems you connected it to and nothing else. You set the budget cap and the rate limits before it runs.

You approve anything irreversible

You choose which steps need a human. Those wait in an approval inbox with the full trace of what the agent did and why. Every run is logged and replayable step by step, which is what an auditor asks for.

AnthropicOpenAIGoogle GeminiMistral AIMetaDeepSeekxAIOllamaAWSMicrosoft AzureGoogle CloudDocker

Your cloud, your keys, your models

Run on our managed runtime, on your own AWS, Azure or GCP, or fully on-premises and air-gapped. LLM calls go through your own API keys. The same agent works in all three, so you’re not locked in on day one.

Four layers

Four layers over the same code

Business, Engineering, Management and Compliance each get the view they need. Underneath, it is one set of automations running on one runtime.

Business view: an automation drawn as a graph next to the chat that built it.
Business

The people who know the process build it.

A process expert describes the process to an agent in plain language. The agent draws it as a graph they can read and correct.

  • See the automation as a graph, step by step
  • Connect Gmail, Drive, Supabase and the rest of their tools
  • Test it with sample data before anything runs for real
  • Request a release when it is ready
Stackbone Studio: one run with its steps, timing and output.
IT / Engineering

Everything becomes code IT owns.

Each automation lands as code in a repository: versioned, reviewable and maintainable. IT decides what ships and operates it in Stackbone Studio.

  • Releases go through the engineering team
  • Every run on the record, with its steps
  • Observability and the runtime in one place
  • No shadow flows outside the engineers’ scope
Management view: adoption, runs, success rate and estimated return per automation.
Management

What exists, what it runs, what it returns.

Team leads see every automation in their department with its adoption, runs, success rate and cost, next to the hours it is estimated to save.

  • Runs, success rate and costs per automation
  • Estimated hours saved and ROI, with the formula visible
  • Custom dashboards built with an analyst agent
Compliance view: a control with its linked evidence and status.
Audit / Compliance

Controls and evidence, on the same record.

Compliance reviews frameworks and controls against the automations that actually run. Stackbone tracks the frameworks; certification stays with your auditor.

  • SOC 2, ISO 27001 and ISO 27701 controls
  • Data retention policies, files and evidence
  • The activity log of who changed what
  • A compliance agent that answers with cited sources
Inside each view

The work each layer does

One automation, seen from four seats.

Connect their own tools.

Email, storage, ERP, LMS and the rest, authorized once and reused by every automation.

Test before release.

Run the automation on sample data and see each step before asking for a release.

Everything deployed, in one catalog.

IT sees every workflow and agent the installation serves, with its last run and outcome.

Return, with the formula.

Estimated hours saved and ROI per automation, with the assumptions behind the number.

Natural language dashboards.

Leads describe the dashboard they need and an analyst agent builds it from the data.

Retention policies.

What data each automation keeps, for how long, and which policy says so.

Answers with sources.

Ask the compliance agent a question and get an answer that cites the evidence it used.

Controls, with evidence.

Each SOC 2 or ISO control shows the evidence behind it and what is still missing.

Put every department on one foundation.

Tell us which processes your teams automate today, and we walk you through the four layers on a call.