DYNO Mapper VS Proofrun

Proofrun's answer:

Because product decisions need more than AI-generated answers or another place to store research.

Proofrun is designed for the work between identifying a problem and deciding what to do about it.

Instead of starting from scratch every time a question comes up, you can build on an existing Discovery, examine competing hypotheses, trace evidence back to its sources, and understand what has changed.

It helps product professionals challenge assumptions, make uncertainty visible, and preserve the reasoning behind their work.

For individual PMs and founders, that means a more structured way to investigate real problems.

For product teams, it creates a foundation for shared context, traceability, and continuity.

You don't need another confident AI answer. You need to understand whether the evidence actually supports it.

Proofrun's answer:

Most AI research tools give you an answer. Proofrun helps you understand how that answer was formed, what evidence supports it, what contradicts it, and what could change it.

Proofrun turns product questions, problems, and opportunities into Living Discoveries that connect competing hypotheses, traceable evidence, contradictions, and research gaps.

With Keep Alive, a Discovery can be revisited as new information emerges, preserving the history of how your understanding evolves.

The result is more than a research report. It's a persistent, evidence-based context for product decisions.

And there's one principle at the heart of Proofrun: AI investigates, challenges, and informs. Humans decide.

Proofrun's answer:

Proofrun is built for people responsible for understanding product problems and making informed decisions.

Its primary audience includes Product Managers, Senior PMs, Product Designers, Product Researchers, and startup founders who need to investigate opportunities, evaluate assumptions, and understand the evidence behind their next steps.

It also serves Heads of Product, Product Directors, and Product Operations professionals looking to improve the consistency, traceability, and continuity of Product Discovery across teams.

Proofrun is particularly relevant for organizations where product research, analytics, customer feedback, and decision context are fragmented across different tools and people.

Proofrun's answer:

Proofrun was born from a problem its founder experienced firsthand while working in technology and product management.

Software development kept getting faster. With AI, building products became easier than ever. But understanding which problems deserved attention, evaluating competing hypotheses, and keeping decisions grounded in evidence remained difficult.

Research was scattered across documents, dashboards, conversations, and people's memories. Valuable context could disappear as teams moved forward.

The question became: what if Product Discovery could remain useful long after the initial research was completed?

That idea became Proofrun.

Built around the concept of Living Discovery, Proofrun aims to preserve the evidence, uncertainty, and reasoning behind product decisions, while keeping that understanding open to revision as new information emerges.

Because building faster only creates value when teams understand where they're going.

Proofrun's answer:

Proofrun is built with a modern, cloud-native architecture designed for AI-assisted research and continuous Product Discovery.

Its main technologies include:

• Next.js, React, and TypeScript for the web application.
• Python for the research and agent orchestration engine.
• Amazon Web Services (AWS) for cloud infrastructure and execution.
• Amazon Bedrock for AI-powered research and analysis.
• PostgreSQL and Amazon DocumentDB for structured and document-oriented data.

The architecture separates the product experience from the research engine, supporting structured investigations, evidence management, and ongoing Discovery reassessment.

Proofrun's answer:

Proofrun is a newly launched platform, currently being tested by product professionals and early users.

We're actively gathering feedback from Product Managers and product leaders to refine the experience and validate real-world use cases.

We don't have publicly announced paying customers to list yet.