AI Analytics & BI, Turn Your Data Into Decisions That Drive Revenue
Intelligent data pipelines, predictive forecasting, and real-time dashboards that give you the insight to act before your competitors see the opportunity.
AI-Powered Business Intelligence: AI-powered business intelligence combines traditional data warehousing and dashboarding with machine learning models and large language models to do things conventional BI cannot: predict future outcomes, identify anomalies automatically, answer natural-language data questions, and surface insights proactively rather than waiting for a human to run a query.
By the Numbers
of data-driven companies outperform their peers (McKinsey Global Institute)
faster decision-making when executives have real-time data vs. weekly reports
average revenue improvement from acting on predictive churn signals (Bain & Company)
average time from data audit to live unified BI dashboard
What We Deliver
Real-Time Executive Dashboards
Unified dashboards in Looker Studio, Tableau, or custom React apps, pulling from GA4, your CRM, ad platforms, and databases into a single source of truth, updated in real time.
Predictive Forecasting Models
ML models that forecast revenue, churn, demand, and campaign performance 30–90 days ahead, built on your own historical data and updated automatically as new data arrives.
Anomaly Detection & Alerts
AI monitors your KPIs continuously and alerts you the moment something unexpected happens, a traffic spike, a conversion rate drop, or a revenue anomaly, before it compounds.
Natural Language Data Queries
Ask your data questions in plain English: 'What drove the revenue increase in Q3?' or 'Which marketing channel has the highest LTV customers?', powered by GPT-4o data analyst agents.
Data Pipeline Engineering
Clean, reliable data pipelines from every source (ad platforms, CRM, payment processors, databases) into BigQuery or Snowflake, so your dashboards are built on accurate, fresh data.
Cross-Channel Attribution
Multi-touch attribution models that correctly assign revenue credit across Google Ads, Meta, email, SEO, and direct, giving you the true ROI of every channel.
Who This Is For
E-Commerce & DTC Brands
Challenge: Revenue data in Shopify, ad data in Meta/Google, email data in Klaviyo, no unified view and no ability to forecast next month's revenue confidently
Solution: Unified BigQuery data warehouse feeding a real-time Looker Studio dashboard with revenue forecasts and channel attribution, board-ready in 30 seconds
SaaS Companies
Challenge: Churn is rising but nobody can identify which cohorts are at risk until it's too late to act
Solution: ML churn prediction model scoring every customer weekly, at-risk accounts flagged in HubSpot for proactive success outreach 60 days before churn
Retail & Franchise Operators
Challenge: Inventory and sales data across 20+ locations not available in real time, requiring weekly manual reports
Solution: Real-time multi-location dashboard with anomaly detection, stock-out alerts, underperforming SKU flags, and location comparison scorecards
Marketing Agencies
Challenge: Client reporting taking 4–6 hours per client per week, pulling data manually from 5+ platforms
Solution: Automated client BI dashboards with white-label branding, clients access real-time performance data self-serve, agencies focus on strategy
Our Engagement Process
Data Audit & Architecture Design
We audit your current data sources, quality issues, and reporting gaps, then design the warehouse architecture, dashboard structure, and model requirements.
KPIs We Report On
- Dashboard data freshness (time lag from source to dashboard)
- Forecast accuracy (MAPE % for revenue and demand models)
- Anomaly detection response time (time from anomaly to alert)
- Data quality score (% of records meeting completeness and accuracy standards)
- Report generation time (hours saved per week on manual reporting)
- Decision velocity (time from question to data-backed answer)
Frequently Asked Questions
Key Takeaways
- ✓A single source of truth, one dashboard everyone trusts, eliminates the endless debates about whose numbers are right in leadership meetings
- ✓Predictive models that act on leading indicators (early churn signals, demand patterns) always outperform reactive reporting on lagging indicators
- ✓Data quality engineering is 70% of the work in a successful BI project, investing in clean pipelines is what makes dashboards trustworthy
- ✓Natural language querying (ask your data a question in English) democratises data access for non-technical leaders, no SQL required
- ✓Anomaly detection that proactively alerts your team is more valuable than any static dashboard, you learn about problems before they compound
- ✓Real-time attribution across channels is the foundation of smart budget allocation, without it, you are making million-dollar decisions with incomplete information
Explore Related Services
Stop Guessing, Start Knowing
Book a free data audit. We'll identify your biggest data gaps, the quickest wins, and show you what a unified dashboard would look like for your business.