How disconnected data can derail modern investigations

Faced with this array of disparate information sources, investigators are forced to piece together timelines, entities, and link charts by hand often with inconsistent results and limited repeatability. Administrative reporting demands combined with rising expectations for speed, accuracy, and auditable decision-making further stretch already limited investigative bandwidth. As data sources expand faster than officers can keep pace, agencies need tools that reduce friction, surface relevant insight quickly, and support defensible, evidence-driven outcomes without adding operational complexity or compromising data security and privacy.

As a distributed search and analytics platform, Elastic brings these isolated, unstructured data sources together via a secure data mesh approach. As a result, investigators can uncover links, patterns, and relationships faster and with greater confidence. Built-in geospatial search makes it easy to surface related activity by location while Elastic’s vector search capabilities enable deep discovery across large volumes of unstructured text. Datasets that include unstructured information like officer narratives, interview transcripts, and witness statements are often where the most valuable signals often live. And Elastic helps make those connections securely.

The Elastic Agent Builder extends this even further by enabling AI-augmented, repeatable investigative workflows driven by task-specific AI agents. Instead of simply retrieving data, these agents can execute multistep reasoning, run predefined investigative checks, correlate findings across sources, and present structured, defensible output. This opens the door to deeper insight and faster research cycles in ways that would be impractical or too time-consuming to perform manually or with traditional tools. The ability to rapidly summarize long-form reports, extract entities, build timelines, and identify potential links meaningfully enhances investigative capacity while maintaining auditability and chain-of-evidence integrity.

These capabilities are designed to augment human investigative judgment, not replace them. Elastic integrates with existing data systems and workflows rather than requiring a rip-and-replace approach, allowing agencies to modernize incrementally while maintaining chain-of-custody integrity, auditability, and courtroom defensibility. The result is a reduction in time spent gathering and synthesizing information, freeing personnel to focus on interviews, validation, and decision-making — the work that actually moves cases forward.

These capabilities are also deployable in offline and fully air-gapped environments, ensuring that agencies with the highest security and compliance requirements can still benefit from modern AI-driven workflows. Elastic remains model-agnostic, giving organizations the flexibility to select the large language models (LLMs) that best align with mission needs, security posture, and procurement constraints. Combined with Elastic’s role-based access control (RBAC) and attribute-based access control (ABAC), agencies can enforce highly granular authorization rules while data-scoping and anonymization ensure that LLMs only receive the minimum information required to perform their task. 

In a modern AI environment, the most successful agencies won’t be the ones with the most data; they’ll be the ones that can connect it, trust it, and act on it faster.

To learn more about how Elastic can speed investigations through data and AI, join the webinar: Law enforcement in the public sector: Breaking data silos for faster, smarter policing.