AI intelligence and human control
AI that helps engineers investigate, challenge and explain.
DAOSoft uses the context of your decision to help develop a reviewable study, investigate permitted evidence and explain analytical results. People review AI contributions and retain decision authority.
Bring a decision question and the constraints on using your data.
Turn an ambiguous request into a study the team can review.
Clarify intent, identify missing scope and propose decision questions. Draft a study plan with evidence needs, analytical methods and activities for the team to refine.
Investigate the evidence and challenge the result.
Retrieve source-linked material from the permitted knowledge context. Flag conflicting assumptions, missing qualifications and differences in applicability.
Explain analytical tradeoffs, sensitivities and conditions that could change the recommendation. Surface potential effects of a new requirement or test result for investigation.
Three modes. Different responsibilities.
- AI Assistproposes, retrieves, organizes and explains within the decision context.
- AI Reviewflags possible gaps or conflicts for reviewers to resolve, with findings attributed to their source.
- Delegated Executionperforms named, authorized and reversible preparation tasks with recorded scope, inputs and outcomes.
A scoped task, not an open-ended instruction.
Illustrative task: prepare a draft evidence summary from two designated sources. The draft carries the relevant references and unresolved qualifications for human review.
Read the diagram
Illustrative workflow using fictional documents, not an executed task or a product screenshot. A person specifies an evidence-summary task using a vibration test report, version 2, and an installation specification, revision 3. The AI-generated draft cites stable operation under vibration from the report and resilient mounting from the specification. Because the report does not describe its test mounting, applicability to the specified installation remains unresolved. The illustrative engineering reviewer retains the draft, requests mounting evidence and leaves the qualification open. The contribution, sources and human disposition remain linked in the decision record. Contribution review is not evidence approval, a requirement waiver or a commitment. References do not independently establish truth or applicability.
DAOSoft links the attributed AI contribution, source versions and human disposition in the decision record. Applicable authorization and record checks govern its admission; those checks do not establish engineering correctness. Numerical results remain tied to their analytical model and run, not to the AI’s explanation.
Explore combinations of engineering alternatives.
Use AI suggestions as starting points for candidate alternatives. Teams define components, compatibility rules and assessment models to explore combinations. Evaluation uses the methods supported by that study and model. A suggestion is not proof of feasibility or optimality.
Set the information and execution boundaries.
Define permitted sources, AI providers, data handling and delegated tasks for the engagement. Critical decision workflows can operate without generative AI.
See an AI-supported evidence review.
Bring a decision question and the constraints on using your data.