The harness for enterprise transformation
AI Transform Studio connects your strategy, architecture, delivery, and knowledge sources, then works the problem with you. The agent plans, runs the analysis across those systems, and builds a living artifact on the canvas while you steer.
Bring your own model keys.
Strategy sits in one place, architecture in another, delivery in a third, and the reasoning behind all of it in pages nobody can query. Before anyone can say what a retirement actually touches, someone spends days reconciling exports.
An epic in Jira, a business capability in the architecture repository, an IT service in ServiceNow, and the decision written up in a page are four identifiers for one piece of change. The integration project that reconciles them outgrows the question it was meant to answer.
Chat hands you a paragraph. The impact analysis, the roadmap, and the visual everyone actually reads still get rebuilt by hand afterwards.
Studio sits above the systems you already run: strategy, architecture, delivery, service, and the knowledge sources where the reasoning lives. People and agents work the same canvas, the way a team works a whiteboard, except one of the participants can read every connected system.
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Connect architecture and strategy repositories, delivery trackers, service management, and knowledge tools like Atlassian and Notion. The agent reasons across them and reconciles what lines up, so the mapping happens per question instead of per integration project.
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This is a harness, not a chat box. It plans the work, keeps a goal, calls tools across your sources, and stays steerable through analysis that takes hours. Watch each step, redirect mid-run, or hold a write at an approval.
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The work lands as a living artifact built from the connected data. Refresh it against source, work inside it during the next session, and let the agent revise it while people are still asking questions.
Same product, three ways in. Architects and transformation leads use it in-house or across client engagements; builders wire it into the organization.
You own the answer when someone asks what a retirement, a merger, or a platform move actually touches. Trace it with an agent across your connected sources, then hand leadership an artifact they can open, drill into, and question.
You run the forum where sequencing gets agreed. Bring one board that business and IT can both read, run the agent live when someone asks what happens if this slips, and carry the same board into the next cycle.
Compose MCP servers, skills, and agents under a harness you control: approvals before sensitive tools, steerable long-running work, and your own model providers inside your organization's boundaries.
Each one is built from the data you connected and worked on together: you and the agent are both on the canvas, in the same artifact, at the same time.
The initiatives, the capabilities they fund, and where work sits now, assembled by the agent from the delivery systems you connected. Move a card; ask it to re-sequence and watch the board change with you.
When programs and initiatives land — and what slips if one branch moves — reworked by the agent while people are still deciding. Presentable, and open to challenge before anyone commits.
Multi-domain views across the estate — business, application, and technology — overlaid by the agent for risk, cost, and age so leadership can act on the hotspots before the investment conversation starts.
A retirement, a platform move, or a merger cut, traced by the agent across what else sits in the path so you see blast radius before anyone commits.
The options, the trade-offs, and the recommendation, written by the agent from the analysis it just ran. Studio checks every cited value against your sources, and approvers sign off on the version they read.
The platform
Architecture repositories inventory the estate. Delivery tools track the tickets. IT operations tools track the incidents and services. All three wait for someone to export, reconcile, and paste the answer into a deck. An agent bolted into a sidebar still finishes in a turn — and you still have to export, again.
Built for the long run — not a turn that answers, stops, and starts from zero.
A teammate you compose — briefed for the estate, not a generic agent that only sees the tool it lives in.
A verdict with its confidence, or a refusal with its reason. Every decision is traced, so the room can check it.
The method your team already uses, assigned on purpose — not a prompt you retype.
A repeating transformation job, run from a template: an agent, a judge, then an agent, ending in a deliverable you can send.
You and the agents work on the stage, and the result is an artifact the room can open. The sources are still on it, and it refreshes against them.
The picture is assembled from connected sources, so the meeting begins at the decision rather than at the data.
Run the agent during the session. Explore a what-if, test a sequencing option, and see it on the canvas before the conversation moves on.
Every source call the agent makes is visible in the run, so you can see how it reached the picture in front of you.
Refresh against source and keep working in the same artifact instead of rebuilding it each time the question returns.
A Jira epic, a business capability in the architecture repository, an IT service in ServiceNow, and the decision written up in a page are four names for one piece of change. Rather than funding an integration programme to reconcile them, the agent reasons across the sources as it works, and every call it makes is visible in the run.
Connect 100+ systems through an MCP server, or add your own custom MCP server.
You connect your own model providers, so inference runs on the contract you already hold and keys stay server-side. Connections are scoped to your organization, sensitive actions wait for a person to approve them, and Studio reads your systems rather than writing to them.
