Business intelligence solutions for everyday decisions
Our business intelligence solutions answer questions in plain language, flag notable changes and deliver reports inside the tools people use. We build around the decisions each answer supports and the data that makes it trustworthy.
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What are AI business intelligence solutions?
AI business intelligence solutions add natural language querying, automated narrative explanation and proactive anomaly alerting to traditional reporting. Instead of making users build or interpret dashboards, business intelligence solutions let people ask questions in plain language. They also push notable changes to people before anyone asks.
Dashboards that were built, launched and abandoned
Most organizations have far more dashboards than anyone uses. Teams built and delivered each one on request, and people opened it for a fortnight. After that, they forgot it and kept asking the underlying questions by email.
The reason is not dashboard quality. Instead, using a dashboard requires three steps: knowing which one, remembering to check it, and interpreting what changed. Most people will not do all three routinely.
Answer questions and push what changed
Natural language querying removes the first two steps: you ask in plain language, in the tool you already use. You then get an answer that shows the query, so you can check it.
Similarly, anomaly alerting removes the third. When something notable changes, the system tells the relevant person and explains what drove it. Nobody has to notice first.
What our business intelligence solutions include
Natural language querying is the visible feature, and it works well on top of a properly defined semantic layer. Without one, the model guesses at what “revenue” means and produces confidently wrong numbers, which is worse than no answer.
Automated narrative is the underrated one. It explains in sentences what changed and what contributed, so a reader does not have to interpret a chart.
Anomaly detection and alerting drive most of the behavior change. That is because they remove the need to remember to look.
None of this replaces a well-built dashboard for people who genuinely use one. Instead, it serves the much larger group who never will.
Our business intelligence services cover custom business intelligence solutions, from BI dashboard development and KPI dashboard development to data visualization solutions your team will actually open.
- Semantic layer defining what metrics actually mean, before any AI touches them
- Natural language querying with the generated query shown for verification
- Automated narrative explaining what changed and what drove it
- Anomaly detection with alerting to the relevant person
- Delivery into Slack, Teams or email rather than a separate BI tool
- Governance so the same question always returns the same definition
Is business intelligence right for your business?
Organizations with substantial reporting infrastructure and poor adoption, which is most organizations with substantial reporting infrastructure.
It also fits teams whose analysts spend their time answering ad-hoc data questions rather than doing analysis. That is a symptom of the same problem.
Business reporting automation suits teams whose analysts spend their week answering ad-hoc questions. Business analytics dashboards and plain-English answers give people the numbers without waiting for a report.
- Companies with many dashboards and low measured usage
- Analyst teams consumed by ad-hoc data requests
- Leaders who ask questions by email rather than checking reports
- Organizations where problems are noticed late in the reporting cycle
- Businesses where the same metric is defined differently by team
- Teams wanting self-service analytics that does not produce wrong answers
What business intelligence can do for your business
Answers without a dashboard
Questions asked in plain language in the tool people already use, which removes the adoption barrier entirely.
Notable changes pushed
Anomalies surfaced proactively rather than waiting for someone to remember to check.
Narrative, not just numbers
What changed and what drove it, in sentences, so nobody has to interpret a chart.
Analyst time released
Ad-hoc question volume absorbed, returning analyst capacity to actual analysis.
One definition per metric
A semantic layer so “revenue” means the same thing regardless of who asks or how.
Verifiable answers
The generated query shown alongside the answer, so users can check rather than trust.
Problems business intelligence solves
Dashboards nobody opens
Reporting built and abandoned. However, delivery into existing tools changes adoption fundamentally.
Analysts answering ad-hoc questions
Capacity consumed by data requests. Self-service querying then absorbs the routine ones.
Problems noticed too late
Issues found in the monthly review. Instead, anomaly alerting surfaces them in days.
Metrics defined differently by team
Three answers to the same question. A semantic layer, by contrast, establishes one definition.
Self-service producing wrong answers
Users building incorrect queries. Governed semantic layers prevent it.
Numbers without explanation
Charts requiring interpretation. Automated narrative explains what changed.
What every business intelligence engagement includes
Everything below is in scope on a standard engagement. In other words, you will not discover an upsell halfway through the build.
Semantic layer definition
Canonical metric definitions, dimensions and relationships agreed with the business before AI touches them.
Natural language querying
Plain-language questions translated to queries, with the generated query shown so answers can be verified.
Automated narrative
Written explanation of what changed, what contributed, and how it compares to prior periods.
Anomaly detection
Statistical detection of notable changes with alerting to the relevant owner rather than a general channel.
Conversational delivery
Available in Slack, Teams or email where people already work rather than in a separate BI tool.
Query governance
Row-level security and permission enforcement so users only query data they may access.
Scheduled reporting
Recurring reports assembled with narrative and distributed automatically.
BI platform integration
Built on your existing warehouse and BI tooling rather than replacing it.
Which AI models and tools do we use for business intelligence?
We are not tied to one vendor. Instead, we pick models and infrastructure on accuracy, cost per task, latency, and where your data may live.
How we deliver business intelligence, step by step
Our BI work follows five stages in a fixed order. You can always see what comes next and what you will get.
Discovery
First, we find which dashboards people actually open, what questions reach analysts, and where metric definitions conflict.
AI Strategy
Next, we rank use cases by cost to build, time to value and savings, and agree canonical metric definitions.
Pilot Build
Then we pilot the top-ranked use case at a fixed scope on your semantic layer, so you see real answers.
Implementation
After that, we connect your warehouse and BI tools, deliver answers in Slack, Teams or email, and train users.
Optimization
Finally, we tune alert thresholds and query accuracy monthly, and report the analyst hours and dollars saved.
How much does a business intelligence project cost?
Business intelligence solutions are priced on your data sources, the metrics that need agreeing and where your team wants answers delivered. You get a fixed written price before we start, and the metric definitions alone often settle long-running disagreements.
Book a free 30-minute call and bring a question your dashboards cannot answer quickly. We will show you how your team could get that answer in plain English, in the tools they already use.
- A written savings estimate before any paid work
- Fixed scope and fixed price, agreed up front
- Full ownership of everything we build for you
- An honest recommendation when the numbers do not work
Figures are internal measurements across recent engagements, reported to every client monthly in writing.
Business intelligence FAQs
Why do dashboards go unused?
Because using one requires knowing which dashboard, remembering to check it, and interpreting what changed. Most people will not do those three steps routinely, however well someone designs the dashboard. The fix is not a better dashboard. Instead, it is answering questions where people already are and pushing notable changes to them unprompted.
Can AI reliably answer questions about our data?
Only with a properly defined semantic layer. Without one, the model has to guess what “revenue” means in your business. As a result, it will produce confidently wrong numbers, which is considerably worse than no answer. That is why we build the semantic layer first. We also show the generated query alongside every answer, so users can verify rather than trust.
Do we need to replace our BI platform?
No, and we would advise against bundling that decision into this one. Instead, we build on your existing warehouse and BI tooling. Platform replacement is a large project with its own risks, so it needs its own justification. Besides, it is rarely the actual cause of adoption problems.
What is a semantic layer and why does it matter first?
It is the canonical definition of what each metric means and which dimensions you can slice it by. It also sets how each metric relates to the others. This matters because without it every question is ambiguous. For example, on a recent engagement, building the semantic layer resolved three long-standing disputes over metric definitions. In each, different reports calculated the same metric differently, producing conflicting numbers in leadership meetings.
How does anomaly alerting avoid becoming noise?
By tuning thresholds per metric to its actual variability. Alerts route to a specific owner rather than a general channel, and we track whether people act on them. People mute an alerting system nobody acts on. Therefore, we start conservative and expand as evidence shows the alerts are useful.
What does AI business intelligence cost?
It depends on your data sources, how many metrics need defining and where answers should be delivered. Most teams start with the semantic layer, which is valuable on its own, then add natural language questions and alerts. Each stage gets a fixed written price first. Book a free 30-minute consultation to scope it.
Ready to scope your business intelligence solutions project?
Book a free 30-minute consultation. Bring one workflow. You will leave with a realistic estimate of what it would cost to automate and what it would save.