Get Better Answers with Fusion Analytics

Turn open-ended conversations into explainable, interactive insight maps. Explore themes, compare segments, and trace every finding back to the source.

Overview

Fusion Analytics ingests conversations from multiple sources and converts open-ended language into topics, standardized semantic units, and traceable evidence. It then layers quality, sentiment, segments, and scoring so teams can explore patterns, compare groups, and defend conclusions with verbatim source context.

Visualization-First

Move from lists to landscapes.

Dimensional

Layer sentiment, engagement, quality, and segments.

Explainable

Every chart opens to the words behind it.

Two Analysis Modes

Fusion Analytics supports (1) respondent-centric analysis for single-participant survey/interview conversations that standardizes and scores responses for comparable distributions, and (2) knowledge-graph analysis for multi-participant dialogue that extracts conversational points with traceable evidence and applies attributes across speakers, topics, and relationships.

Mode 1 — Single-participant conversations

Best for surveys and interviews with a question-response exchange pattern, where one respondent maps to one conversation. Fusion treats the respondent and conversation as directly coupled.

Mode 2 — Multi-participant conversations

Best for open-form dialogue with multiple speakers and variable formats. Fusion uses a flexible methodology that produces graph objects and attributes across multiple node types.

Single Participant Analysis

Fusion ingests single-participant conversations from Curious AI, external uploads, and integrated systems via API, using parsing templates to normalize formats into a consistent interviewer-interviewee and question-response structure.

Fusion evaluates response quality and signal strength, reveals co-occurrence and correlation patterns across topics and segments, and maintains full traceability so every distribution, bucket, or insight links back to the exact verbatim messages and context.

Responses: combine related messages into a composite response
Buckets: group conceptually similar responses into high-level buckets
Response Items: break responses down to their primitive parts for more granular resolution

Multi-Participant Analysis

Fusion ingests multi-participant dialogue from meetings, chats, workshops, and facilitated sessions. It identifies speakers, turn structure, and context so free-form conversation becomes analyzable without forcing a rigid survey format.

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Fusion applies configurable attributes across Conversations, Points, Participants, and Topics. This makes it possible to compare perspectives, detect alignment and tension, and filter analysis by role, cohort, or context.

Segments: classifications that are defined or emergent from the underlying data that enable visual and analytical groupings
Scales: scored values against an user defined continuum from 0 to 1
Vectors: multi-dimensional qualities that categorize entities into classes with polarity and strength of expression

Fusion produces outputs built for decision-making: agreement and tension summaries, topic landscapes, participant viewpoints, and evidence-linked reports. Every insight remains traceable to the exact source context.

Points: the claims, viewpoints, proposals, and observations expressed in the dialogue
Evidence: exact utterance spans that support each point for auditability
Alignment: clusters of shared viewpoints across speakers and cohorts
Tension: contradictions and competing narratives by topic and segment
Dynamics: how points shift over time, across conversations, or between groups

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Drill Down

From signal to sentence in one click. Open any node to see the exact verbatim words behind a pattern and the metadata that supports it.

Raw Responses — timestamped, speaker‑labeled, and evaluation scores.
Response Primitives — standardized semantic units to retain nuance and fidelity.
Sentiment & Tone — emotional polarity, intensity, class, attitude, and other dimensions that reveal feelings.
Engagement Measurements — how the individual's engagement changes during the survey or interview.
Quality Metrics — amplify stronger signals and dampen low-confidence data.

Correlations

Examine relationships across responses and topics, identify underlying components, and detect patterns and outliers.

Reporting and Sharing

Configure Fusion to your organization.

Text Reports — define or import map structures that fit your needs.
Scoring — define custom parameters for scoring qualitative or numerical data.
Sentiment — Measure sentiment toward specific topics with polarity, intensity, and class labels.
Extraction — Extract specific entities from conversations.
Presentation — Show insights directly from Fusion using configurable report formatting and organization.
View-only Link — Share interactive results securely with view-only authenticated access links.