Five data sources.
One connected picture of your market.
Healthcare and pharma brands sit on enormous amounts of intelligence — conversations, social data, research papers, search trends, and medical claims — but it lives in separate tools and separate reports. BGBX.ai connects all five layers into one place, so the patterns that span them finally become visible.
Huge amounts of data. None of it talking to the rest.
"No single data source tells the whole story. The value comes from connecting them — so a conversation, a search trend, and a research paper all add up to one clear picture."
Data scattered across separate tools
Recorded conversations, social media, scientific publications, search trends, and medical claims data each live in their own tool and their own reporting workflow. No single place shows all of them together.
Each source only tells part of the story
A social spike means something different when it aligns with a wave of new research and a rising search trend. On its own, any one source is easy to misread — the full picture only emerges when they sit side by side.
Connections get missed entirely
When data never sits side by side, the patterns that span multiple sources are invisible. A rising search trend that mirrors a shift in patient conversations and a new cluster of publications — nobody joins those dots because nobody can.
Pulling it together by hand is slow
Analyst teams manually reconcile reports from multiple vendors. By the time the picture is assembled, the market has moved on. Brand and strategy decisions are made on incomplete, delayed intelligence.
The 3D Data Stack — five layers, each answering a different question.
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01
Said→ Transcription Hub
Voice of the customer — what people actually say.
The Transcription Hub analyses spoken conversations and recorded discussions to capture the language, concerns, and framing that patients and healthcare professionals use in their own words. This is the raw, unfiltered voice of the market.
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02
Shared→ Social Hub
Experience of the customer — what people talk about in public.
The Social Hub reads social media to surface emerging topics, audience reactions, and shifts in the broader conversation around a therapeutic area, brand, or condition. It captures how the public experience of a category is evolving in real time.
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03
Studied→ Literature Hub
Research & science — what the evidence base says.
The Lit Hub tracks scientific papers and publications to follow where the research is heading, which institutions are most active, and which topics are gaining momentum in the medical literature. It gives brand teams a live view of the scientific landscape behind their category.
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04
Secret→ Search Hub · Web Behaviour
Search patterns — how audiences explore topics over time.
The Search Hub and Web Behaviour tools follow how patients and doctors search for information — what terms they use, what they click, and how their exploration of a topic evolves. Search behaviour often signals changing awareness or concern before it surfaces anywhere else.
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05
Substantiated→ Claims Hub
Behaviour of the customer — what medical claims data shows.
The Claims Hub draws on medical claims data for an evidence-based view of what is actually happening in treatment and prescribing — grounding the platform's softer signals in hard, real-world behaviour data.
Transcription Hub
Spoken conversations and recorded discussions, processed into structured insight. Feeds the Said layer.
Social Hub
Social media monitoring across platforms. Emerging topics, reactions, conversation shifts. Feeds the Shared layer.
Literature Hub
Scientific publication tracking by institution, journal, country, and topic. Feeds the Studied layer.
Search Hub
Search term analysis and trend tracking across audiences and markets. Part of the Secret layer.
Web Behaviour Hub
How audiences navigate and explore topics across the web over time. Completes the Secret layer.
Claims Hub
Medical claims data for real-world treatment and prescribing behaviour. Feeds the Substantiated layer.
Two dashboards that turn connected data into clear market intelligence.
A map of the market built from real conversations.
This dashboard turns recorded conversations into a structured view of the market — grouped by therapeutic area (oncology, neurology, cardiology, and more), pulling in material from YouTube, podcasts, and other channels.
At a glance it shows how many patient and HCP comments have been gathered, which medical specialties the conversations touch, how data volume is changing over time, and which sources and facilities it comes from.
A dedicated Rx Mode section analyses how healthcare professionals approach treatment and prescribing decisions — scoring seven decision styles (data-driven, directive, innovation-driven, mission-driven, partnership, prestige-driven, tradition-driven) as heat maps broken down by therapeutic area.
- Patient and HCP comment volumes by therapeutic area
- Medical topic and specialty breakdown
- Data volume trends over time by source
- Source and facility origin of conversations
- Rx Mode: 7 prescriber decision styles as heat maps
- How doctors approach patient management decisions
- Total publications by country and institution
- Publication activity by year
- Number of countries per study
- World map of research activity by market
- Topic map: AI, genetics, and key focus areas
- Most active institutions and most-cited journals
The scientific landscape, mapped and searchable.
This dashboard makes sense of the published literature — showing how many papers have been analysed, where the research is coming from, and which institutions and journals are driving it.
A world map shows research activity by region, helping teams spot the markets that are leading a particular field. A topic map highlights the themes gaining the most attention, such as AI applications, genetics, and other areas of active investigation.
The result is a live, navigable view of the scientific context surrounding a brand or therapeutic area — without manually reading and cataloguing hundreds of papers.
Three analyst products that go from data to deliverable.
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01
→ Analyst Product 01 · Project Control Room
Set up the project before you begin.
The Project Control Room is where teams define the scope and parameters of a piece of work before sending it into the analysis tools. It ensures that Deep Insight and Lexicon IQ start with clear, consistent inputs — the right therapeutic area, the right audience, the right timeframe.
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02
→ Analyst Product 02 · Deep Insight
Build a richer understanding of patients and providers.
Deep Insight is where the platform's connected data layers produce structured analysis of what patients and healthcare professionals actually think, feel, and do. It goes beyond surface metrics to produce the kind of layered audience understanding that informs strategy, messaging, and brand positioning.
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03
→ Analyst Product 03 · Lexicon IQ
Understand the language — and sharpen the messaging.
Lexicon IQ maps the words audiences actually use and shows how they relate to one another across the data. For healthcare and pharma brands where the right language is critical — both for regulatory reasons and for genuine resonance — this turns vocabulary analysis into a practical messaging tool.
A scalable data pipeline built for fast analytics — invisible to the user.
For the everyday user, all of this simply means the dashboards stay fast and up to date — no matter how much data is added.
Apache Airflow
Manages the automated data pipelines that ingest, process, and route information from all six hubs into the platform's unified data store.
Google BigQuery
Stores the processed data at scale. Built for the large, analytical query loads that healthcare intelligence platforms generate — fast reads across billions of rows.
Cube
Sits between BigQuery and the front-end dashboards, providing a consistent, pre-aggregated semantic layer so all metrics are defined once and always calculated the same way.
Metabase
Delivers the interactive dashboards and visual exploration layer that analysts and brand teams use every day — connected directly to the Cube semantic layer for live data.
Need to connect scattered data sources into one intelligence platform?
We build data platforms that pull multiple sources together, build semantic layers on top of them, and surface the patterns that matter — as clean, fast dashboards your team can actually use.
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