See what changed. Understand why it matters.
Explore patterns across time, location and connected sources. Give analysts the context to investigate what needs attention.
Ask better questions
Explore connected data through SQL, PRQL and supported natural-language queries. Investigate the information behind an observation.
Build on what works
Bring query results into Raven dashboards or external business intelligence and data science tools, including a Postgres-compatible interface.
Controlled AI enrichment
Explore Insight AI bricks for managed model deployment and data enrichment. Choose the models, controls and review points your use case requires.
What does this signal actually mean?
Follow the illustrative scenario to see how data, context and a human decision fit together.
Raven/Mission workspaceOperational overview
Priority reason: This observation involves a critical screening asset. Human review is required.
Your implementation
Supported connections and workflow options depend on the chosen modules and deployment. Bring a representative source and use case to your demo.
Your evidence
Evaluate the source references, query behavior and review steps with your own acceptance criteria. Simulated screens do not establish product performance.
Your next step
Discuss the configuration, integrations and deployment model that fit your organization with DTACT’s team.
Bring your challenge.
See what connects.
Explore how Raven can connect your data,
your people and your next decision.