SERVICE
Reports and insights, on tap, from your data.
We plug into your databases, document repositories and operational systems, and deliver the analyses your team would build if they had the headcount. Every output evidence-backed, every dataset stays with you.
Most organisations have more data than they can analyse. The reports that would matter (explaining churn, surfacing fraud, validating a hypothesis, preparing a board paper) sit in the backlog because the analytics team is fully booked maintaining the dashboards that already exist. Hiring more analysts is slow and rarely fixes the real bottleneck: half the work is data engineering, not analysis.
Analytics as a Service is the alternative. We do the data work. You get the answer.
A senior analytical team, data engineers, knowledge graph specialists, domain analysts, engaged on a defined scope. We bring our own platform (Networks Notebook, GraphRAG, Text Business Intelligence) and use it to deliver against your questions.
Engagements are scoped around outcomes, not hours. A typical engagement looks like one of these: a forensic analysis of a specific dataset, an ongoing dashboard built and maintained on top of your operational data, a one-off investigation into a specific business question, a recurring report cycle (monthly, quarterly) for compliance or executive review.
Output is evidence-backed. Every chart, every conclusion, every recommendation links to the underlying data. You get the report, the dataset and the explanation of how it was produced.
Three engagement modes, sized to fit the question.
In every mode the data stays in your environment. We can work on-premise, in your cloud, or in a sovereign environment. We are deployment-agnostic by design.
Forensic-grade methodology. Every output is auditable. We are accustomed to analyses being scrutinised by regulators, courts and internal compliance teams. The same standard applies to your work.
Knowledge graph as default. Our analyses are built on a structured graph of your data, not a flat warehouse. That means we can connect signals across silos that traditional BI cannot, text and transactions, internal data and external sources, structured and unstructured.
Senior team, no juniors. Engagements are staffed with people who have shipped this kind of analysis in regulated environments. No layered teams, no offshore handoffs.
Platform plus people. You get our platform during the engagement. If the engagement converts to a long-term need, the platform stays. If it does not, the analyses remain reproducible against your data.
In banks and payment institutions to build AML and fraud analytics on top of existing transaction systems: graph-based detection that catches what tabular tools miss. In publishing and media to extract operational insights from production data, scripts and editorial archives. In public-sector institutions to support analysis of large grant or programme datasets. In any organisation where the analytical question is hard, the data is messy, and the team is busy.
The honest comparison is with three alternatives. Hiring more analysts in-house is slow and only solves the bandwidth problem, not the data engineering problem. Engaging a generalist consultancy gets you slides; we deliver running analyses you can re-run. Buying a BI tool gets you dashboards over the data you already have; our work surfaces what your current systems cannot see.
We sit between these. We are operators, not advisors. The deliverables are running systems, not recommendations.
Do you take our data, or work in our environment?
Your environment. We connect to the data where it lives, on-premise, cloud, sovereign, air-gapped. Data does not move unless you decide it should.
Who owns the deliverables?
You. Reports, datasets, dashboards and code are yours. Where we use BCNN platform components, those remain licensed for the engagement and beyond if you continue using them.
How is this different from hiring a consultancy?
Engagements are outcome-scoped, not hour-billed. Deliverables are working analyses, not slide decks. Our team are practitioners who have shipped this kind of work in regulated environments.
What does it cost?
Single-question investigations start at €15,000 depending on scope and data complexity. Recurring and embedded engagements are quoted on the analytical cycle and team size required.
Can it convert to in-house?
Yes. We are designed for this. Many engagements end with the analyses being handed over to an in-house team. We document, we train, we step away.
Tell us the question and the data. We will scope an engagement, propose a deliverable and a timeline.
From email threads and spreadsheets to a dedicated web app. One timeline replaces every status meeting.
Read more CASE STUDY · MEDIAFact-verification time dropped substantially, cutting production costs. Characters, locations and plot threads, queryable in natural language.
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