Predictive Analytics & Data Intelligence
Turn historical noise into forward-looking decisions. Churn before it happens, demand before it spikes, risk before it costs you.
See Around Corners
Every business generates data. Most drown in it. We build predictive analytics systems that transform historical data into forward-looking intelligence — so you can act before events happen, not after. Customer churn before it occurs. Demand spikes before they hit. Equipment failures before they cause downtime. Fraud before it drains your accounts. Our models don't just predict — they prescribe actions, quantify confidence levels, and integrate directly into your decision-making workflows.
RAG Knowledge Bases: Your Data, Instantly Queryable
Your company's collective knowledge lives in documents, wikis, Slack threads, emails, and databases — scattered and unsearchable. We build Retrieval-Augmented Generation (RAG) systems that make all of it instantly queryable in natural language. Ask "What's our refund policy for enterprise clients?" or "Show me all deals lost to Competitor X in Q3" and get accurate, cited answers in seconds. RAG systems eliminate knowledge silos, accelerate onboarding, and give every team member access to institutional intelligence.
Decision Intelligence: From Dashboards to Direction
Dashboards tell you what happened. Decision intelligence tells you what to do. We build systems that go beyond reporting — they analyze situations, evaluate options, model outcomes, and recommend actions with quantified confidence. A pricing engine that recommends optimal price points by segment. An inventory system that suggests reorder quantities based on demand forecasts and supplier lead times. A customer success platform that flags at-risk accounts and prescribes intervention strategies. This is analytics that drives action, not just observation.
What You Get
- Data audit and pipeline architecture
- Custom predictive models (churn, demand, risk, fraud, LTV)
- RAG knowledge base with natural language search
- Decision intelligence dashboards with prescriptive recommendations
- Real-time alerting and automated action triggers
- Data warehouse and ETL pipeline setup
- Model monitoring, drift detection, and retraining pipelines
Expected Outcomes
- Predict customer churn with 80–95% accuracy
- Forecast demand with 15–30% better precision than baseline
- Reduce knowledge lookup time by 90%+ with RAG systems
- Automate data-driven decisions with confidence-scored recommendations
- Turn raw data into a strategic competitive advantage
Predictive Analytics — Common Questions
How much data do we need for predictive analytics?
It depends on the use case. Some models work with as few as 1,000 records. Others require months of historical data. Part of our engagement is assessing your data landscape and recommending what can be built now versus what requires additional data collection.
What is a RAG system and why do we need one?
RAG (Retrieval-Augmented Generation) combines a search engine with an AI language model over your private data. Instead of generic AI answers, you get responses grounded in your actual documents, policies, and data — with citations. It eliminates knowledge silos and makes institutional knowledge instantly accessible.
How do you ensure model accuracy and prevent drift?
We implement continuous monitoring with drift detection, automated retraining pipelines, and human-in-the-loop validation for high-stakes predictions. Models are evaluated against held-out test data and business outcomes, not just technical metrics.
Initiate a Project
Tell us what you're building: automation, marketing, software, or full-stack transformation. We respond within one business day.