The Challenge
Research is only valuable if it reaches the people who can act on it. Yet in most organizations, that journey from raw findings to organizational action is where insights go to die.
Researchers and analysts face a familiar set of obstacles:
- Findings are fragmented across formats — Survey responses sit in spreadsheets, interview notes live in docs, and user journey maps are buried in a design tool no one else opens
- Synthesis is a manual bottleneck — Pulling disparate artifacts together into a coherent narrative requires hours of manual organization before any insight work can begin
- Stakeholders can’t engage with raw data — Sharing a folder of research artifacts doesn’t give stakeholders a way to explore or question the findings meaningfully
- Insights decay before they’re applied — By the time a coherent presentation reaches decision-makers, the context has shifted and the research feels stale
The consequence is a research function that produces more output than the organization can absorb.
The Autohive Solution
Autohive agents act as the connective tissue between your research data and your stakeholders, automatically organizing findings into Miro boards that tell a coherent story.
Multi-Source Research Aggregation
Agents pull research artifacts from connected sources—survey platforms, note-taking tools, interview repositories, analytics systems—and bring them onto the Miro canvas in a structured format. Survey response tables, journey diagram data, and observational notes all arrive pre-organized rather than requiring manual import.
Pattern Visualization and Clustering
Rather than dumping raw data onto the board, agents identify structural patterns—grouping related observations, surfacing common themes across interview participants, and mapping conceptual relationships between findings. The result is a knowledge map stakeholders can navigate rather than a data dump they have to decode.
Persistent Reference Architecture
The Miro board isn’t just a deliverable—it becomes a persistent knowledge repository. Agents maintain the board as new research comes in, adding fresh findings to existing clusters and updating patterns as the evidence base grows. Stakeholders can return to the board weeks later and find it enriched, not abandoned.
Benefits
- Faster time to insight — Research findings become navigable and shareable hours after data collection rather than days after manual synthesis
- Higher stakeholder engagement — A visual knowledge map invites exploration in a way that a PowerPoint deck or a shared folder simply doesn’t
- Reduced research waste — Findings that would previously sit unused become accessible reference material the organization can return to over time
- Cumulative knowledge building — Each new research project adds to an existing body of visual knowledge rather than starting from scratch
How It Works
- Connect your research stack — Link your survey tools, note-taking platforms, and data repositories to Autohive alongside Miro
- Define your knowledge architecture — Set up the board sections, cluster types, and tagging conventions that match your research practice
- Set aggregation rules — Tell the agent which data sources to pull from, what to organize as tables versus diagrams versus document items
- Agent builds and maintains the board — Incoming research gets organized, clustered, and added to the evolving knowledge map automatically
- Stakeholders explore directly — Decision-makers access the Miro board to navigate findings, drill into specific user journeys, and reference observations in context
Getting Started
- Sign up at app.autohive.com
- Connect the Miro integration from the marketplace
- Configure your research data sources and knowledge map structure
- Deploy your agent and turn every research project into an accessible organizational asset
