InsightPoint

The answer was in there — buried under the search.

Intelligence analysts work across enormous datasets: conversations, phone numbers, devices, social accounts, and the relationships between them all. Finding a meaningful pattern meant reviewing hundreds of conversations by hand, manually connecting entities, and hopping between disconnected tools.

Traditional keyword search made it worse: you had to already know exactly what you were looking for. Answering a real question meant reading vast amounts of content and piecing together relationships across multiple datasets yourself.

From search results to an investigation.

That insight reframed the whole design. Instead of returning a list of isolated matches, the system needed to surface evidence-backed findings, the conversations supporting them, and the networks of people and devices connecting them. We were designing an investigation workflow, not a search box.

The result is a conversational platform: analysts query in plain language and get instant summaries, network insights, and explainable results — each one traceable back to its source.

Surface the answer; keep the depth one click away.

The dataset holds a huge amount of interconnected information, and showing it all at once would bury the analyst. So the experience surfaces information in layers — the answer first, then the supporting evidence, then the original conversations — letting people go deeper only when they need to.

From content to connections.

Analysts can pivot from reading content to mapping relationships. Using phone numbers, devices, social accounts and operational data, they generate network graphs that reveal potential connections and the key actors inside them — the questions keyword search could never answer, like how are these devices, numbers and people connected?

Show the working, not just the verdict.

Every insight links back to the conversations it came from. Rather than presenting conclusions as facts, the platform exposes the supporting evidence and source material — so analysts can validate findings themselves and keep their confidence in the system. In a government accountability context, that traceability isn't a nice-to-have; it's the requirement.

Faster answers, fully accountable.

InsightPoint showed how AI-assisted search and investigation can help analysts uncover relevant intelligence far faster — while keeping the transparency and traceability the work depends on. No query language, one unified workflow, and a source behind every claim.