Agentic BI and decision intelligence
Answers from your data in plain language, and the dashboards to act on them
Decisions wait for reports
Executives ask a simple question and wait days for an analyst to answer it. Dashboards multiply, each with its own numbers, and few show what needs attention now.
Meanwhile the data your customers would value stays locked inside, because building analytics into a product looks like a separate project.
What you get
Questions in plain language
Business users who ask questions in plain language and get answers they can trace.
Decisions in view
Executive dashboards and command centres that show what needs a decision today.
Analytics your customers use
Analytics built into your customer products, as a service or a new revenue line.
What we deliver
Conversational BI and AI data analysts
Natural language to SQL and to insights: users ask in their own words, and an AI analyst queries the governed data and shows how it got the answer.
Executive dashboards and command centres
Dashboards and operational command centres built around the decisions each leader makes, with alerts when a measure moves outside its range.
Automated operational reporting
Recurring operational and management reports produced automatically from the same definitions, instead of assembled by hand each period.
Embedded customer-facing analytics
Analytics inside your portals and apps, so customers and partners see their own data, with access limited to what each may see.
Self-service data monetisation platforms
Platforms that package your data and insights as products customers can explore themselves or subscribe to.
How it works
Start from the decisions
We agree which decisions, questions and users matter most, and the measures that support them.
Agree the definitions
We put the measures in a semantic layer, so a dashboard, a report and an AI analyst all mean the same thing.
Build and test with users
We build the first dashboards and question sets, and test answers against figures your teams already trust.
Release and extend
We release to a first group, review what they ask and where answers fall short, then widen access.
Technologies and standards
Answers come from a governed semantic layer over your lakehouse, with access rules enforced before any query or model runs. AI answers show the query and the data behind them.
- Languages
- SQL
- Data and analytics
- Power BI
- Tableau
- Methods and practices
- Conversational BI
- Natural language to SQL
- Command centres
- Embedded analytics
How to start
Clients with defined measures and data sources go straight to a proposal. Where the data still needs mapping, we start with the data platform work it depends on.
What happens next
Pre-consulting session
A free 30-minute online pre-consulting session: we go through your goals, systems and constraints.
Readiness review
In a free 48-hour readiness review, a Principal Architect checks your project against the 6-point Definition of Ready and recommends the track that fits.
Choosing the track
Scope-ready projects receive a binding proposal within 3–5 business days. Concept-stage projects start in the Blueprint Studio. A live system that is failing, undocumented or needs integration starts with a diagnostic of 1–2 weeks. The Blueprint Studio and the diagnostic each have a fixed fee, quoted in the proposal.
Delivery in five stages
Mobilisation, sprints with live demonstrations, integration and hardening, acceptance and go-live, then managed services. After launch comes a warranty period, then optional support and maintenance.
AI-native product teams
Managed, cross-functional pods of senior engineers, equipped with agentic coding and QA harnesses.
Questions and answers
Can we trust answers from a conversational BI tool?
Only if they are traceable, so every answer shows the query it ran and the data it used. It reads from agreed definitions in a semantic layer, and we test it against figures your teams already trust.
What does natural language to SQL mean?
A user types a question in plain language, and the AI analyst turns it into a database query, runs it on governed data and explains the result. Users need no SQL, and analysts spend less time on routine requests.
Will users see data they should not?
No. The same row-level and role-level access rules apply to dashboards, reports and AI answers, so each user sees only what they may see.
Do we have to replace our current BI tools?
Not necessarily. We can add conversational analysis and shared definitions on top of the data you already have, and retire overlapping dashboards over time.
Can we offer analytics to our own customers?
Yes. We build analytics into your portals and apps, with each customer limited to their own data. Where your data has value to others, we can package it as a self-service product.
What if our data is not ready?
Then we fix the foundation first. Dashboards and AI analysts are only as good as the data beneath them, so we start with the sources, quality checks and definitions they need.
Who owns the dashboards and models?
You do. The code, definitions, dashboards and documentation we produce for you are yours once each milestone is paid.
Start with a conversation, not a contract.
Tell us what you need to build, connect or secure. An architect goes through it with you, then recommends where to start.
What happens next
Agreeing a time
Our team emails you to agree a time for the session.
Pre-consulting session
A free 30-minute online pre-consulting session: we go through your goals, systems and constraints.
Readiness review
In a free 48-hour readiness review, a Principal Architect checks your project against the 6-point Definition of Ready and recommends the track that fits.
Choosing the track
Scope-ready projects receive a binding proposal within 3–5 business days. Concept-stage projects start in the Blueprint Studio. A live system that is failing, undocumented or needs integration starts with a diagnostic of 1–2 weeks. The Blueprint Studio and the diagnostic each have a fixed fee, quoted in the proposal.