One platform to run your AI transformation.
AI transformation means changing how work gets done with AI. HDATF brings the company's work, knowledge, AI tools and operating support together. The goal is to keep implementation, daily operation and improvement in the same place.
A shared operating space for each company
An AI run belongs to a company task. Its sources, permissions, execution record, cost and output need to stay connected, even when the tool or person changes.
Keep the work running after adoption.
The service model combines paid platform use with operating support. We define the work to improve, connect the required information and tools, then review operation and results with the customer. Fees and responsibilities are agreed for the chosen scope.
Discuss platform adoption and operationOne task becomes an ongoing operation.
Define the work
Agree the task, expected output, roles, budget and scope of support.
Connect the company
Prepare the workspace, source documents, access rules and tools needed for that task.
Run and review
Check progress, outputs and actual usage. Track failures and the changes they require.
Improve and expand
Use validated methods in the next task. Add further workflows under the same operating rules.
Work modules on the same foundation
ATF Works provides the shared workspace. LabChin is the first specialist module, being developed to help researchers check consequential assumptions before costly work. Evidence, tools and decisions stay connected to the same platform direction.
ATF Works
A workspace for teams to manage projects, share documents and review progress against daily work records.
Available work tools
- Calendar, projects and daily work logs
- Documents, wiki, approvals and messages
- Assistant work inside each person's permissions
Prepare a weekly project review.Example workflow
- Before
- Ask each person for updates, search the chat for decisions, then rebuild a report.
- What the team gets
- Project tasks, daily logs and related documents in the same workspace. The team reviews the work with its records at hand.
LabChin
A research module in development to check important assumptions before costly work and keep decisions connected to evidence.
Research workflows in development
- Identify the assumptions that could change the direction
- Choose a valid check before committing resources
- Keep evidence, uncertainty and the researcher's decision together
Continue a study from the previous report.Example workflow
- Before
- Read the old files again to recover the method, check the data and work out what remains.
- What the team gets
- A report linked to sources, current inputs and the next questions. Explore the sample package to see the research workflow we are developing.
The technology behind shared operation.
We are developing Company Brain to connect company knowledge, sources and permissions. The harness manages AI tasks and checks their outputs. Together, they build on the workspace's existing documents and work records.
Discuss platform adoption and operation
Bring a recurring task and the documents it depends on. We will define the scope, access rules and review criteria with your team.
ContactAX case studies