Assumption-driven planning and decision workspace

Reduce decision rework while keeping assumptions and evidence visible. For product teams and innovation leads turning ideas and project information into organized, shared visual work, convert notes, project data, client conversations and linked AI services into a reviewed decision workspace with scored assumptions and source-linked evidence. The benefit is a testable hypothesis, measured through decisions closed per planning cycle and assumptions retired with evidence; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect notes, project data, client conversations and linked AI services, then follow this sequence: 1. Arrange project information on a shared visual canvas. 2. Edit the same canvas with multiple people in real time. 3. Track project data in tables and timelines. 4. Turn unstructured notes into formatted briefs and reports. 5. Convert sticky note ideas into interactive prototypes. 6. Flag assumptions as risky until enough evidence supports them. 7. Evaluate evidence with a separate AI service from the one that generated the assumption. 8. Surface evidence, key metrics, progress scores and risks behind each suggestion. Resolve uncertain cases with qualified reviewers, approve reviewed decision workspace with scored assumptions and source-linked evidence, and measure decisions closed per planning cycle and assumptions retired with evidence against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use a separate AI service to evaluate evidence independently from the AI that generated the assumption. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed workspace schema and linked AI services; final decision and evidence checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve source attribution, quotation accuracy and usage permissions. Named owners approve substantive changes and decision scope. One fixed workspace schema and linked AI services; final decision and evidence checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One fixed workspace schema and linked AI services; final decision and evidence checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: arrange project information on a shared visual canvas; edit the same canvas with multiple people in real time. Support the remaining modules with operator review: track project data in tables and timelines; turn unstructured notes into formatted briefs and reports; convert sticky note ideas into interactive prototypes; flag assumptions as risky until enough evidence supports them; evaluate evidence with a separate AI service; surface evidence, key metrics, progress scores and risks. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Customer-owned notes, project data and client conversations. Cloud asset storage, design-file import/export, cloud account connections and preferred AI services such as OpenAI and Azure. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Assumption board and canvas, Evidence and decision review, Client and delivery view. Use a thumbnail gallery for projects, a large central canvas with tables and timelines, and a right-hand panel for assumptions, evidence, risks and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant assumption or asset. Make the task-specific outcome reviewed decision workspace with scored assumptions and source-linked evidence visible beside its evidence, review state and value baseline.