Stradviso & Decision Studio

The description states that Stradviso & Decision Studio consists of:

• An authenticated Business OS backoffice
• A role-aware customer project workspace
• Project collaboration and controlled record workflows
• Decision Studio, which governs how AI-generated inputs are handled in decision-making processes

Decision Studio is described as a system for handling unclear client questions by:

• Returning one focused blocking question when information is missing (no scenarios or approvals)
• Presenting three bounded scenario options when sufficient context exists
• Requiring human approval for any change, with deterministic application code checking authorization and freshness before applying updates
• Ensuring that model output has no direct database authority

The system uses:

• PHP 8.3, Laravel 13, Livewire 4, MySQL, SQLite, JavaScript, Tailwind CSS 4, Vite, PHPUnit
• Codex and GPT-5.6-sol via OpenAI Responses API with store:false
• Synthetic project data for demonstrations

Not evidenced No actual product usage, customer feedback, or commercial traction is described.

The author positions Stradviso as a solution to the problem of unclear client requests leading to unaccountable decisions. The key claim is:

"AI proposes. Humans decide."

This positioning emphasizes human control over AI-generated outputs and accountability in project decision-making.

The project evolved from an idea developed before Build Week, with the core functionality (Decision Studio) being built during the event. It was not intended as a full business OS but rather as a proof-of-concept for one specific boundary — how to manage AI-assisted decisions without allowing them to write directly to project records.

Inference The positioning reflects an attempt to differentiate from generic AI tools by focusing on governance and traceability in decision-making workflows.

Not evidenced No claims about market fit, competitive advantage, or adoption beyond the author's own description.

The target customer is described as:

• Clients who ask ambiguous questions that affect multiple parts of a project
• Project teams working within structured environments where decisions must be accountable and traceable

The system is designed for:

• Project collaboration across email, messages, calls, meetings, and documents
• Situations where context gets lost or an idea becomes a promise before consequences are understood

Not evidenced No specific customer segments, personas, or use cases beyond the synthetic examples provided.

The description does not contain any information about:

• Revenue streams
• Pricing models
• Customer acquisition strategies
• Monetization plans

It also does not mention whether there are any existing customers or paid users.

Not evidenced No business model or pricing evidence is provided.

Technical stack includes:

• PHP 8.3, Laravel 13, Livewire 4, MySQL, SQLite
• JavaScript, Tailwind CSS 4, Vite, PHPUnit
• Integration with Codex and GPT-5.6-sol via OpenAI Responses API (store:false)
• Reproducible tests, evidence, privacy controls, and release safeguards

The system is described as:

• Having deterministic application code that checks authorization and freshness before allowing updates
• Using bounded allowlists for changes (Decision, Risk, Milestone)
• Implementing stale-context refusal with zero writes if the context has changed since approval
• Supporting recovery through clearing old approval states

Not evidenced No information about scalability, performance metrics, or production deployment.

The description indicates:

• The project was built during Build Week (July 2026)
• A separate public website project began after the submission period opened
• Synthetic demo data is used for walkthroughs
• No real-world customer handling or commercial validation is claimed

Not evidenced No evidence of traction, revenue, customers, or adoption beyond synthetic demonstrations.

The description does not provide:

• Information about competitors
• Market analysis
• Competitive positioning
• Differentiation from similar tools in project management or AI-assisted decision-making

Not evidenced No competitive landscape or benchmarking data is available.

Key risks and open questions include:

• Lack of real-world validation: All evidence is synthetic and self-reported.
• Single-person team: Only one member (Stefan Raijmakers) involved in development.
• No commercial traction: No mention of customers, revenue, or usage beyond the author’s own claims.
• Limited scope: The system only supports a narrow set of record types (Decision, Risk, Milestone).
• Dependency on AI output quality: Model output can be incomplete or wrong; human approval remains mandatory.
• No external integrations: CRM platforms and other systems are not integrated.

Inference The project may struggle to scale without further development or validation from actual users.

1. What specific problems do you observe in current project collaboration workflows?
2. How do you plan to validate the effectiveness of Decision Studio with real clients?
3. Are there any early adopters or pilot customers using this system?
4. What are your plans for expanding beyond the current limited record types (Decision, Risk, Milestone)?
5. How will you ensure consistent quality and reliability of AI-generated inputs?
6. What is your roadmap for integrating with external systems like CRM platforms?
7. How do you intend to scale beyond a single developer?
8. Have you considered how this system would behave under high-volume or concurrent decision-making scenarios?